A Comprehensive Review of IoT Standards: The Role of IEEE 1451 in Smart Cities and Smart Buildings

Highlights

What are the main findings?

• Interoperability is paramount in the context of communication between transducers. This paper aims to demonstrate the potential of the standard IEEE 1451 in resolving compatibility issues and its implications for IoT applications, particularly in the domain of smart buildings.
• We outline a framework that promotes the harmonisation of IoT applications. This harmonisation is achieved by bridging the use of different communication protocols, thereby creating an interconnected system.

What are the implications of the main findings?

• This paper provides a review of the problems related to the lack of interoperability between transducers in IoT applications, thereby creating a plug-and-play architecture that fosters ease of use and flexibility.
• IEEE 1451 enables the creation of harmonised, flexible, and compatible systems that foster interoperability among transducer networks.

Abstract

The increasing demand for IoT solutions in smart cities, coupled with the increasing use of sensors and actuators and automation in these environments, has highlighted the need for efficient communication between Internet of Things (IoT) devices. The success of such systems relies on interactions between devices that are governed by communication protocols which define how information is exchanged. However, the heterogeneity of sensor networks (wired and wireless) often leads to incompatibility issues, hindering the seamless integration of diverse devices. To address these challenges, standardisation is essential to promote scalability and interoperability across IoT systems. The IEEE 1451 standard provides a solution by defining a common interface that enables plug-and-play integration and enhances flexibility across diverse IoT devices. This standard enables seamless communication between devices from different manufacturers, irrespective of their characteristics, and ensures compatibility via the Transducer Electronic Data Sheet (TEDS) and the Network Capable Application Processor (NCAP). By reducing system costs and promoting adaptability, the standard mitigates the complexities posed by heterogeneity in IoT systems, fostering scalable, interoperable, and cost-effective solutions for IoT systems. The IEEE 1451 standard addresses key barriers to system integration, enabling the full potential of IoT technologies. This paper aims to provide a comprehensive review of the challenges transducer networks face around IoT applications, focused on the context of smart cities. This review underscores the significance and potential of the IEEE 1451 standard in establishing a framework that enables the harmonisation of IoT applications. The primary contribution of this work lies in emphasising the importance of adopting the standards for the development of harmonised and flexible systems.

1. Introduction

The growing demand for automation in smart cities, coupled with the large-scale use of sensors in these environments, has given rise to a pressing need for efficient communication between Internet of Things (IoT) devices. To streamline the process of large-scale use of sensors and actuators in environments requiring automation, it is essential to enable effective communication between these devices. The interaction between devices is made possible through the communication protocols which establish the rules for organising and transmitting information. Communication protocols are the medium by which information is exchanged and processed between devices, thus defining the type of communication via software, hardware (wired or wireless), or a combination of both [1].

Nonetheless, the use of heterogeneous wireless sensor networks and the adoption of diverse sensors from different manufacturers can compromise data interchangeability, giving rise to incompatibility issues [2]. The deployment of wireless networks is often hindered by these types of issues, and thus needs a more streamlined configuration process for transducers in IoT applications, as well as an interface that enables interoperability between different IoT devices. A proposed solution for this challenge involves the creation of a system that enhances interoperability and flexibility through the establishment of fundamental components that enable compatibility with devices from different manufacturers. Standardisation accelerates the sharing of common elements across IoT systems, thereby promoting scalability and interoperability [3,4]. To address this issue, the IEEE 1451 standard has been devised to harmonise smart transducer networks, thereby providing a solution to the lack of interoperability between devices [5].

Syed et al. [6] provide a deep discussion of the technologies employed in smart cities, ranging from the collection, transmission, and storage of data to the analysis of the strengths, weaknesses, opportunities, and threats. According to these analyses, one of the weaknesses and impediments in the deployment of IoT systems is caused by the heterogeneous environments of the technologies employed. As a result of not having compatible standards that enable the use of varied communication protocols and different hardware, IoT systems are not easily expanded, causing constraints to the systems’ scalability and interoperability.

The review made by Ali et al. [7] provides an extensive overview of the protocols employed in IoT and their respective common application in smart cities. The authors also provide a list of protocols and standards used in the different physical, network, and application aspects. The authors present a discussion of the issues in IoT with respect to IoT application protocols and issues in IoT for smart cities. One of the key issues addressed is that mobility, reliability, security, privacy, energy efficiency, scalability, management, availability, and interoperability are affecting the development of smart cities.

The survey written by Lee et al. [8] presents two barriers for IoT applications and smart cities: interoperability and security. The authors refer to the importance of interoperability and security in the IoT market, as well as to what standards have been developed to resolve them. It is important to underline that, in their work, one finding is that interoperability standards can aid in achieving interoperability between heterogeneous IoT systems if they are developed using the same standard. The authors also note that “Interworking and interoperability are required among standards to accomplish standard-based security and interoperability in IoT systems.”

The authors Rawajbeh et al. [9] reviewed IoT applications and their corresponding challenges and solutions. The authors state that the main challenges in IoT applications that impede the stable use of these systems are security, heterogeneity, interoperability, and scalability. Since the most significant obstacle comes from the heterogeneity of devices, an improvement would be to use a standard that unifies different types of devices from different vendors. The authors conclude that scalability and other challenges in IoT systems deployment are correlated, with one causing the other. The solution to resolve the challenges should be to create more capable, adaptable, and compatible devices, in addition to the need for standards that unify IoT devices from the different manufacturers and different communication protocols employed.

A keyword analysis using VOSviewer software [10], with a search query “IoT” AND “Smart cities” AND “Smart Buildings” AND “Sensors” AND NOT “AI” AND NOT “convolutional neural network”, and with the help of the SCOPUS database, with the intention of understanding the working interrelations and highlighting their importance, was conducted. We filtered keywords with a minimum of five occurrences to prevent the relation of unnecessary keywords and remove non-related terms. This search resulted in a total of 222 keywords, of which the most common keywords observed were ‘internet of things’, ‘smart city’, ‘intelligent buildings’, ‘automation’, ‘smart homes’, ‘energy utilisation’, ‘network security’, and ‘wireless sensor networks’.

In Figure 1, one can observe that the ‘smart city’ keyword assumes a key and central role in the vast concept of ‘internet of things’, while some of the important related keywords worth noting are as follows: ‘intelligent buildings’, ‘smart homes’, ‘wireless sensor networks’, and ‘sustainable development’.

Observing Figure 2, there is a direct relation from ‘intelligent buildings’ to ‘internet of things’, and from ‘smart city’ to the latter, with connections to ‘smart homes’, ‘network security, ‘wireless sensor networks’, ‘energy utilisation’, ‘sustainable development’, and ‘sensor nodes’, with it also being important to note ‘interoperability’, thus prompting the importance of relationships between these terms.

This paper focuses on the review of the importance of interoperability in IoT applications, i.e., “the capability of two or more networks, systems, devices, applications, or components to externally exchange and readily use information securely and effectively” [11]. This manuscript reviews and underlines the need for standardisation, considering the creation of uniform systems that enable the use of different technologies (communication protocols and transducers from different manufacturers) with ease of integration.

This paper reviews the standards employed in IoT systems [6,8,12,13,14,15,16,17,18,19,20,21,22,23,24] and their application in various smart cities components and focuses on how the deployment of the IEEE 1451 standard can aid heterogeneous IoT applications in smart cities. The following numbered list highlights some of the issues in IoT applications related to transducer networks:

1.

Although there exist many semantics for transducer communications, the lack of its usage results in the absence of a language that describes what certain data received or transmitted in the transducer networks portrays.

2.

The diversification of transducers delivered by different manufacturers and several types of transducers results in limited interoperability in data exchange between smart transducers.

3.

There is a need for a common interface that enables a way of connecting several types of transducers and provides support for communication between devices of various communication protocols.

4.

There is a lack of interoperability in transducer networks, which affects the scalability of IoT systems, resulting in a need for a system that provides ease of configuration for transducers.

The purpose of this paper is to provide a review of the problems arising from transducer networks in IoT applications which affect smart cities. It also highlights the importance and the potential of the standard IEEE 1451 in providing a framework that promotes the harmonisation of IoT applications by addressing the compatibility of devices from different vendors in IoT applications, particularly in the domain of smart cities. The main contribution of this work is to emphasise the importance of adopting the IEEE 1451 standard to enable the creation of harmonised flexible systems, which facilitates the creation of a compatible system that fosters interoperability among transducer networks.

The paper’s main contributions and novelties are as follows:

1.

It introduces one of the necessary components of interoperable transducer networks, with the use of the sub-standard IEEE 1451.0, which introduces the Transducer Electronic Data Sheet (TEDS). This sub-standard defines the common functions and a transducer data sheet that stores valuable information (such as a few manufacturers, the type of communication, and the parameter read) about the set transducer, enabling the information from the transducers to be comprehensible.

2.

It considers the absence of a common interface, it offers a solution using the IEEE 1451.0 sub-standard, which defines a middleware component that provides a way to connect diverse types of sensors and actuators while also enabling different communication protocols to be used.

3.

With the introduction of TEDS, transducers will need dedicated non-volatile memory to store the TEDS information, or a file delivered by the manufacturer to the user (Virtual TEDS), which will allow for the NCAP to read the TEDS and send the necessary commands to configure the transducers, which enables plug-and-play capabilities and the ease of scalability of transducer networks.

The remainder of this paper is organised as follows: Section 2 briefly identifies and analyses the research works related to this topic. Section 3 presents smart city components and identifies some applications, as well as the standards used. The IEEE 1451 family of sub-standards is presented in Section 4, showing its fundamentals, organisation, and key components.

2. Identified Related Research Works

There are studies that highlight the lack of interoperability in IoT systems and restrictions and challenges that impede the employment of IoT systems to enable smart cities and related concepts, such as smart industry and smart farming, and others. In this context, several studies have been conducted, as is discussed in the following paragraphs.

Mylonas et al. [25] presented a comprehensive review of the employment of digital twins (DTs) in smart manufacturing and key differences in employment in a smart city setting, thus focusing on how DTs can be integrated in smart cities and what the challenges are implied with the integration of these systems. The authors highlight several challenges that hinder the deployment of DT systems; some of the challenges listed are interoperability between sensors, standardisation, security, and privacy.

The paper written by Madolia et al. [26] provides an IoT solution for shelter home security and welfare, exploring the use of IoT technology and sensors for smart monitoring of shelters. It is emphasised that the need for sustainable cities and communities can be satisfied by the integration of adequate and affordable housing and shelters by applying IoT technology; smart monitoring within shelters can be achieved with low-cost computing, assisting people to enjoy relaxed and convenient living within shelters and smart homes. IoT technology has the potential to help shelter home residents with internet access, enabling them to connect with family, access medical assistance, and obtain weather updates. The study points to the need for standardisation among protocols and connected devices within smart networks, thus enabling a solution for smartly managing devices.

The survey elaborated by Sharmila Kumari et al. [27] focuses on the IoT application layer’s security, highlighting the several types of attacks and the security of the systems that enable IoT in smart cities and their varied components. The authors discuss the protocols used in IoT applications in the application layer, while also sharing the importance of IoT security, especially given the annual increase in the number of IoT applications. Finally, they highlight the challenges in IoT application layer security, ranging from heterogeneity due to the diverse nature of hardware, operating systems, communication protocols, and security capabilities across different IoT devices. Also, the lack of standardised security practices results in the lack of a solution to establish consistent and reliable security across IoT devices. Updated devices and data confidentiality were also highlighted as some of the main challenges in the security of IoT applications.

In the survey performed by Iqbal et al. [28], the authors present the semantic web approaches used in IoT applications in smart cities that focus on enabling semantic interoperability. Highlighting the importance of relating the meaning of data and the data collected, also known as metadata, can create difficulty in managing data as the growth in data increases, and highlighting that, with this absence, there is a restriction to interoperability between smart components of a smart city. Furthermore, the authors propose an IoT system that interconnects the healthcare system to airlines, proposing a system that shares the status of COVID-19 in patients, streamlining the process of updating the health status of patients, removing unnecessary formalities, and their current COVID-19 status.

Meydani et al. [29] reviewed solutions and frameworks that enable IoT in a smart city domain. This review gave a structured view of the possible IoT applications in smart cities and how the IoT architecture is divided into layers: perception/sensing, transportation/network, middleware/processing, application, and business. The authors give a detailed overview of each layer, characterising the sensing layer as the physical layer that is composed of sensors and actuators responsible for sending and receiving data. The authors refer to the middleware layer, responsible for data aggregation, since, due to the heterogeneous environment of an IoT application (varied types of devices and communication protocols), the middleware layer must enable interoperability among devices at the various levels. The application layer provides users with the requested services, output formats, and applications. Finally, the authors state that, due to the presence of many different IoT protocols and devices, the lack of interoperability is affecting the integration of IoT solutions in smart cities. The scalability of IoT systems will allow for micro-service-oriented architectures, event-driven/data-driven applications, and more sustainable solutions in smart cities, resulting in a better quality of life.

In another work, Belli et al. [30] provide a review of smart cities and their components, with a focus on improving the sustainability of a smart city, giving the example of Parma, a city in Italy that is already implementing IoT technology with the goal of raising the quality of life of citizens in the municipality of Parma. The authors provide an overview of the backbone infrastructure responsible for enabling connectivity in IoT devices, highlighting that the number of heterogeneous connected devices is increasing yearly. This work elucidates the most pertinent IoT protocols and their characteristics (range and data rate), and it shows the already deployed IoT applications by the municipality of Parma, ranging from examples like magnetic parking sensors and parking status sensors. The authors present some of the challenges in smart cities; one important thing to note is the barrier to the development of IoT solutions due to the lack of interoperability, underlining that there is a necessity to coordinate data collection and data analysis.

Related to this subject, Pliatsios et al. [31] provide an overview of semantics and its use in smart cities. The authors highlight that, for the growth of a smart city, and due to data variety and quantity, it is essential to find a solution that allows for the integration of different IoT solutions while achieving semantic interoperability. It also portrays what areas semantic interoperability has been employed in and what technologies enable it; some of the applications are smart transportation, smart buildings, smart healthcare, environmental pollution, smart grids, smart water, and smart government. The authors conclude that semantic interoperability might benefit from the use of artificial intelligence, machine learning, and IoT to improve data collection and analysis. This underscores the importance of creating more open and standardised data formats and protocols to enable data exchange between different devices.

The survey performed by Peralta Abadía et al. [32] explores IoT frameworks for smart cities and the applicability of IoT. They present IoT framework architectures and the respective layers of each architecture, exploring the function of each layer. The usual IoT framework architecture is divided into a sensing layer, a network layer, a middleware layer, and an application layer. The authors give an extensive overview of the applications, network and messaging protocols used, IoT device types, services provided by the middleware layer, and challenges met (scalability and heterogeneity/interoperability). The authors highlight that interoperability and hardware/software dependency must be considered to allow for a platform that enables the heterogeneity of components, avoiding vendor lock-in, thus supporting the use of different sensor data formats.

Choudhary et al. [33] provide an overview of IoT in smart agriculture, providing an example model of an IoT system for agriculture and the possible applications of IoT in agriculture. This system is divided into the collection of data, transfer of data, analysis of data, and visualisation of data. The authors provide a comparative analysis of the communication technology in IoT and a layered view of web services and IoT, explaining the role of each layer. The work also highlights the possible applications of IoT in other domains, covering the healthcare sector, wearable accessories, traffic monitoring sector, and others. In their conclusion, they discuss the problems inherited by IoT applications, some of the most relevant being standardisation and interoperability; the authors note that interoperability between IoT devices and platforms remains a challenge.

From the collection of papers of related works [6,7,8,9,25,26,27,28,29,30,31,32,33], it is possible to perceive that the lack of compatibility in IoT devices results in scalability, non-interoperability, and security issues, which impact the deployment of IoT systems in smart cities.

Table 1. Summary of related works focusing on interoperability features in IoT systems implemented in smart cities and related concepts.

Ref.	Research	Limitations
[6]	Technologies employed in Smart cities (such as the collection of data and transmission), while also providing a Strengths/Weaknesses Opportunities/Threats analysis.	Interoperability of networks. Incompatible sensor standards. Networks attacks/data theft.
[25]	Review of the employment of DT in smart manufacturing and key differences in employment in a smart city setting.	Interoperability between sensors. Standardisation. Security and privacy.
[26]	IoT solution for shelter home security and welfare, exploring the use of IoT technology and sensors for smart monitoring of shelters.	Standardisation among protocols. Standardisation of devices within smart networks.
[27]	IoT application layer security, highlighting the several types of attacks and the security of the systems that enable IoT in smart cities.	Heterogeneity of hardware and communication protocols. Different security capabilities across different IoT devices. Low computational power.
[28]	Semantic web approaches used in IoT applications in smart cities that focus on enabling semantic interoperability.	Interoperability between smart components.
[29]	Solutions and frameworks that enable IoT in a smart city domain. Giving light to the different IoT protocols and devices raises interoperability issues affecting the integration of IoT solutions in smart cities.	Lack of interoperability with use of different communication protocols and IoT devices.
[30]	Review of smart cities, with a focus on improving the sustainability of smart cities, giving the example of Parma, which is implementing IoT technology to raise the quality of life of its citizens.	Lack of interoperability in IoT solutions. Vendor lock-in. Lack of open standard-based devices.
[31]	Overview of the use of semantics in smart cities, noting that it is essential to find a solution that allows for the integration of different IoT solutions while achieving semantic interoperability.	IoT device diversification. Need for standardised data formats and protocols.
[32]	Explores IoT frameworks for smart cities and the respective layers of each architecture, exploring the function of each layer.	Lack of interoperability results in vendor lock-in hardware/software dependency.
[33]	IoT in smart agriculture, using the example of an IoT system for agriculture.	Lack of standardisation and interoperability between IoT devices and platforms.
[7]	Overview of the protocols employed in IoT and their respective common application in smart cities.	Security. Privacy. Scalability and Interoperability.
[8]	Presents two barriers to IoT applications and smart cities: interoperability and security. Underlines that interoperability standards can aid in achieving interoperability between heterogeneous IoT systems.	Lack of interoperability in heterogeneous IoT systems. Lack of security in IoT devices.
[9]	Reviews IoT applications and their corresponding challenges, stating that the main challenges in IoT applications impede the stable use of these systems.	Security. Heterogeneity. Interoperability and scalability.

summarises these related works, focusing on their features in terms of interoperability and their limitations.

3. Smart Cities Components, Applications, and Standards

In this Section, the IoT applications for smart city components are explored, shedding light on the type of technology used (such as the type of sensors, actuators, standards, and protocols for communication).

3.1. Standard Deployment in Smart City Components

A smart city is divided into several components. We in [6] divide and explain the many components present in a smart city. We also discuss the key role of IoT in smart cities. IoT creates an environment where everything is connected. Adding the large-scale use of sensors and actuators to a smart city allows for the varied components of a smart city to be automated; with the use of communication protocols, IoT devices can be interconnected [34]. Figure 3 shows the diverse components of a smart city.

Communication between devices relies on communication protocols that define how the data is exchanged; by means of standardisation, it is possible to ensure reliability and efficient data exchange in communication protocols. A protocol that is not standardised cannot ensure communication with devices of various technologies. Standardisation enables reliability by defining the guidelines to follow. Thus, in the context of communication protocols, standardisation enables interoperability by defining specifications for the solutions based on set standards. The set of guidelines determined by the standards allows for the communication protocols to operate with maximum efficiency while ensuring interoperability. Standards enable protocol stacks with a reliable exchange of data, allowing for the information sent from one device to another across different communication layers not to be lost or corrupted. Standards support scalable solutions, providing the base for the construction of the desired solution. In the varied paradigms of smart cities, Industrial Internet of Things (IIoT) and IoT, there are many standards that are the backbone of the construction of scalable solutions; some frameworks (collection of standards) offer solutions that provide a interoperable platform for applications in these domains, such as oneM2M [35], Eclipse sensiNact [36], IoTivity [37], and FIWARE [38].

Figure 4 shows some of the standards used in the previously referred paradigms [6,18,20,21,22,23,24,25,26,27,28,29,30,31,32], although it is important to note that the primary focus of this study is on the standards employed on the physical layer of the ISO-OSI model [39].

Other standards are merely referenced; they are not thoroughly explored in this work. However, some are explored in these articles [6,8,12,13,14,15,16,17,18,19,20,21,22,23,24].

As depicted in Figure 4, smart cities can utilise a multitude of standards across their diverse components, enabling communication and security tailored to the specific applications and constraints. To give a brief example of the standards employed in a normal application, Figure 5 details the standards, parameters, and sensors employed in major smart city components, namely smart buildings, smart plants, or smart infrastructures, and their related smart services.

Examples of smart plants/infrastructures in smart cities are gas [40], energy [41], and water distribution facilities [42], and the sensor networks infrastructures for public transportation and traffic management systems [30,43,44]. Examples of smart services supported are the traffic light and parking lot management [30], charging stations for electric vehicles, detection of faults in local electric grids and water distribution networks [6], particularly in pumping and water treatment stations [29], and comfort parameters related to air conditioning and air quality [45] in buildings, and the interconnection of all of these, fostering the concept of smart living.

3.2. Applications in Smart Cities

To provide a detailed overview of the existing standards and their use in different domains of a smart city, a review of existing IoT applications based on large-scale use of sensors was carried out on the various components of a smart city to find the common standards used to enable communication between the different sensor nodes. These will be shown in the following pages, starting with Section 3.2.1.

3.2.1. Smart Agriculture

Enabling smart agriculture, Sharma et al. [46] propose an experimental IoT solution to monitor soil in agricultural settings. The proposed system includes a temperature sensor to measure soil temperature; a Nitrogen Phosphorus Potassium (NPK) sensor to measure quantities of nitrogen, phosphorus, and potassium, which are essential for plant growth and lastly; and a soil moisture sensor, which is used to inform when there is a necessity to enable a water pump. To send data to the server, the authors use an ESP8266 Wi-Fi module, enabling communication and the data extracted to inform the server of the crop field soil status to be remotely monitored.

Cornei and Fosalau [47] provide a cheap solution for IoT in agriculture, creating a system for collecting data and storing it to support farm management. The nodes’ structure is integrated with a variety of sensors, including temperature, humidity, moisture, pressure, and light sensors, and also a power supply, which is divided into solar panels, a charging circuit, a Lithium Polymer (LiPo) battery, and a super capacitor. Finally, the standards used to enable communication were Wi-Fi and HyperText Transfer Protocol (HTTP) in the case of the ESP32 microcontrollers, which forwarded the data directly to Google Sheets. For STM32 LoRa, User Datagram Protocol (UDP), TCP, and HTTP were used in conjunction with a LoRa Gateway and the server The Things Network (TTN), which forwarded data into Google Sheets. The Wi-Fi sensor nodes had higher transmission capacity and were more cost-effective compared to the LoRa sensor nodes. The tests proved the efficiency of the sensors, and the collection of data was accurate.

Enriko and Gustiyana [48] reviewed the potential use of Wi-Fi HaLow in agriculture and smart cities in Indonesia. The authors state the many IoT applications in agriculture, including Unmanned Aerial Vehicle (UAV) farming, monitoring farms, precision farming, tracking and tracing, supply chain management, aquaponics farms, and monitoring forestry. And they studied the efficacy of Wi-Fi HaLow in smart agriculture, finding that, due to the limited range of Wi-Fi-based IoT systems, there results in a higher cost to implement a solution based on Wi-Fi. A solution to this is the employment of Wi-Fi HaLow; it provides up to 2 km in range with a clear line of sight and maintains effective performance in short-range without a direct line of sight. The authors state that Wi-Fi HaLow eliminates the need for proprietary hubs and gateways, allowing for a single access point to over 8000 IoT devices and, in conjunction with the ultra-low power consumption of Wi-Fi HaLow devices, can operate for extended periods without the need for maintenance.

3.2.2. Smart Industry

To enable environmental sustainability, Saivarun et al. [49] developed an IoT system that tracks harmful gases, integrating gas sensors, temperature sensors, and humidity sensors to monitor factories in real-time. The IoT devices implemented are an Arduino Uno, responsible for the sensors, and a NODEMCU connected to the Arduino via UART. The NONEMCU sends data via Wi-Fi to the Cloud, which is sent to the factory server and the Tamil Nadu Pollution Control Board (TNPCB) government server. This data is showcased in a website, and if the pollution level has exceeded a threshold value, the TNPCB has access to an ON and OFF button that can cause a power outage at the factory.

The study performed by Awad et al. [50] presents a system for monitoring and controlling movable harbour cranes. To monitor the cranes, the system is composed of weight sensors and angle position sensors. Incorporated with each crane is a Programmable Logic Controller (PLC). The PLC handles the collection of data and sends it to a PC NI OPC (National Instruments Open Platform Communications) server on a PC. The information is then sent via serial communication to the Arduino, which then sends information to the ESP32 incorporated with a Wi-Fi module capable of uploading the data to the ThingSpeak channel cloud, enabling the remote monitoring of the harbour crane.

3.2.3. Smart Infrastructure

Pies et al. [51] present a wireless sensor application for geotechnical monitoring and structural diagnostics. With the use of LoRa, Intelligent Quick Reliable Framework (IQRF), and NB-IoT, the system employed allows for varied coverage ranges with efficient remote monitoring. The authors used accelerometers, temperature, Linear Variable Differential Transformer (LVDT), and hydrostatic sensors. In one system, the authors deploy three sensor nodes to monitor a rock massif stability with the creation of a LoRa network and a LoRa TTN gateway via a Raspberry Pi and an LTE modem. The sensor nodes monitor the rock formation instability, water level, and the movement of the rock. The other system is deployed in a water tower measuring the tower tilt; this system is employed via an IQRF network, with a Raspberry Pi as the network coordinator and communication gateway. The authors highlight the importance of monitoring geotechnical and other structures, and, with the solution employed, create a maintenance and risk management application.

To detect the damage to structures, AbdelRaheem et al. [52] developed an IoT solution capable of monitoring structure health. The authors utilised the ESP-NOW for short-range communication between nodes due to its efficient low-power communication and used the Transmission Control Protocol/Internet Protocol (TCP/IP) and cellular (4G) for long-range communication (central node and gateway). To monitor the structures, accelerometer sensors were deployed, which handled sending the data according to the vibration of the structure. This data was forwarded to a server, where, posteriorly, it was run in MATLAB through a damage detection algorithm. The algorithm identifies vibration-based damage by calculating a change in mode shape through the modal assurance criterion, the natural frequency drop, and mode shape curvature damage, which is identified by the curvature damage indicator that denotes the relation between the stiffness and curvature of the structure.

Kamal et al. [53] present how Vehicular Ad Hoc Networks (VANETs) can have an important role in intelligent transportation by providing comfort and safety to people in traffic jams or disaster-prone areas. With the integration of the standards IEEE 1609 and IEEE 802.11p, which ensure wireless access in vehicular environments, point-to-point communication is supported by the Dedicated Short-Range Communications (DSRC), which enables Vehicle-to-Vehicle (V2V) and Vehicle-to-Infrastructure (V2I) communication. The authors propose a portable medical system on wheels that provides high-quality healthcare and immediate response to patients in need of help in emergency situations. Providing first aid and collecting health information through wearable sensor devices and monitoring the patient’s vital signs while transporting the patient to the healthcare facility.

Barrero et al. [54] provides a networked transducer system for intelligent transportation systems based on IEEE 1451 standard, implementing an IEEE 1451-compliant mobile environmental sensor network (ESN) for urban pollution monitoring in the city of Asuncion based in public transport vehicles, and an artificial-vision-based equipment based in VisioWay was modified in accordance with the standard to apply real-time traffic control. This application implemented the sub-standards IEEE 1451.0 and IEEE 1451.5, which support the use of Wi-Fi for the wireless sensor node. The proposed framework simplifies the equipment’s connectivity into a VANET and to the internet based on the HTTP web services established in the IEEE 1451.0 standard.

3.2.4. Smart Energy

With the intent of enabling real-time data to consumers, Marroquin et al. [55] built a IoT solution that enables voltage, current, and power-supplied measurements. This is performed with the development of two printed circuit boards, with one being for the energy metre circuit that is connected to the Photon via Serial Peripheral Interface (SPI). Photon is a microcontroller with an STM32F205RGY6 core and an embedded Wi-Fi module and allows for communication via an Inter-Integrated Circuit (I²C), SPI, and Universal Asynchronous Receiver Transmitter (UART). The data extracted from the energy metre circuit is then displayed in a Light Crystal Display (LCD) to show power consumption without the need for an internet connection. The user can also use a graphical user interface to access the current measurements via the Particle platform. Photon can interact with the Particle cloud, publishing the data collected by the respective sensors.

Hou et al. [56] showcase a solution to self-sufficient sensor nodes, highlighting that such a solution solves the need for the usual exchange of batteries, supporting a lower need for maintenance. The application at hand is composed of an MSP430F1611 that enables low power consumption. It was integrated via SPI communication with a Texas Instruments CC2420. This transceiver operates at 2.4 GHz within the Industrial, Scientific, and Medical (ISM) frequency band. To manage energy harvesting and supply the IoT node, it uses TI’s BQ25505, which provides two battery interfaces used to connect a Li-ion battery and a Lithium Thionyl Chloride (Li-SOCL2) battery in case of the need for a backup power solution. It concluded that the node communication capability has good isotropic consistency and can effectively communicate with different nodes.

Norman et al. [57] provide a system for monitoring parameters in power distribution transformers, offering a solution that ensures power grid reliability with fault detection through real-time monitoring, thus allowing for the development of smart grids. The system is composed of voltage sensors, current sensors, and a temperature sensor to monitor body and oil temperatures. To provide fault protection, a relay system composed of a transistor and a 5 V relay was implemented. In addition, a 2A fuse was added to ensure excessive current fault tolerance. An Arduino Nano collects data from the sensors and forwards this data to the ESP32 microcontroller, the ESP32, which, via sends, was connected to the Blynk Platform. To detect transformer status, there is a current fault function, a detect over-volt and under-volt function, an earth fault, and, finally, a temperature fault. These functions allow for the user to know the possible error occurring, extending the lifespan and reducing maintenance costs.

3.2.5. Smart Transportation

Following the Sustainable Development Goals (SDGs), smart transportation in smart cities should improve the lives of its citizens. Thus, the creation of systems that enable urban centres to deal with traffic problems and the flow of transport could impact pollution and public transportation [6,30].

To control the flow of traffic, the use of sensors or drones is a possibility, as shown by Prabha et al. [44], although a standard that can be employed could be Wireless Fidelity (Wi-Fi) in cases including the necessity of a high-data-rate, coming at the cost of higher power usage. Other options include Long Range (LoRa) communications for monitoring roads across a wide area, due to its effective range of communication. In the case of an application where real-time vehicle tracking and the range is higher than the effective range of LoRa, the employment of Long-Term Evolution (LTE) or Narrow Band Internet of Things (NB-IoT) would be recommended.

Belli et al. [30] present a few applications that were deployed by the municipality of Parma. The city has implemented six LoRaWAN gateways, enabling applications of parking lot space management. The use of a magnetic parking sensor node allows for the detection of the status of the parking lot. For parking lot management, another sensor node is employed; based on optical technology, it retrieves the status of different parking stalls with a defined timestamp. For traffic management, there is a vehicle passage counting node, returning the number of vehicles that passed in a predefined period. To measure possible intense traffic, it was implements a sensor node that retrieves the average acoustic pressure level.

The paper performed by Matyakubov and Rustamov [43] is an example of a smart transportation system; the authors propose a smart bus system composed by smart bus stations, smart bus stops, and smart buses. Each of these components is composed of various wireless and embedded sensors. The solution to connect the network of sensor nodes is to use Wi-Fi hotspots in bus stops, stations, and buses. With respect to the smart bus, the smart buses would be battery-powered, promoting zero-carbon emissions, and all buses would have a Global Positioning System (GPS), allowing for their location to be tracked in real-time. In smart bus stops, the current location of all buses is shown on display screens, allowing for commuters to know the exact location of the buses. It also introduced the idea of introducing a smart card with Radio Frequency Identification (RFID) or Near-Field Communication (NFC), which enables a smart queue system. Finally, the smart bus station manages the bus fleet, including maintenance and service facilities. Stations would be the central hub, receiving all of the information from the different sensor nodes about the buses and passenger numbers, allowing for dynamic scheduling and route adjustments.

3.2.6. Smart Building

A paper authored by Hamzah and Abdul-Rahaim [58] demonstrates an IoT system capable of improving building security by providing a smart fire alarm system architecture. The system is composed of three sensor nodes, two of which are ESP32 modules: one equipped with sensors and the other with GPS. The sensors equipped are a flame sensor, a gas sensor, a temperature sensor, and a humidity sensor. The ESP32 has built-in Wi-Fi, allowing for connection to the internet; the information collected is sent to the remote xy cloud server, and, in the case of a fire, a Telegram bot sends information detailing the fire occurring (its location).

The authors Rosati et al. [59] aimed to develop an integration between IoT sensor networks and Building Information Modelling (BIM), with a specific focus on air quality parameters including monitoring, temperature, humidity, pressure, Volatile Organic Compounds (VOC), eCO2, IAQ (Indoor Air Quality), Hydrogen, and Ethanol. The standards they used are all based on open broker-based technologies such as MQTT. The data dashboard, designed to visualise real-time data and historical data series, is based on web applications over HTTP. The authors chose to use an ESP8266 microchip that integrates a microcontroller and a Wi-Fi module. Subscribing the node to the master broker is an initialisation process in which the single IoT sensor connects to a Raspberry Pi 4. When the node is connected to the IoT infrastructure, the logic for updating the BIM model is based on a request from the gateway and a response from the node. The research project led to the creation of a sensor hub modelled in BIM, proving the validity of the concept.

The study carried out by Zebani and Er [60] provides an IoT solution that optimises energy usage within buildings. To this effect, the authors have developed an IoT-based system that utilises a NodeMCU microcontroller in conjunction with the Blynk platform via Wi-Fi connectivity. The building’s appliances, including the air conditioning, water heater, television, and lighting systems, are connected to the control board. The building owner is then able to monitor and control the status of the appliances via the Blynk app via Wi-Fi. The security system utilises sensors, such as the DHT22 and gas and flame sensors, which trigger real-time alert messages to the owner via the Blynk app if critical values are detected by the sensors. The findings of the present study demonstrate a substantial impact on energy savings, leading to a reduction in energy consumption and an enhancement in the security of the building.

Authors Loukil et al. [61] created an IoT system for smart homes, capable of being suitable for people of all ages, being able to detect falls and sense fire, hazardous gases, and earthquakes. It has an ESP32-12F as the main chip, which is capable of using the TCP/IP protocol stack, and sends the information to the public cloud through MQTT. The Arduino board, which collects temperature and humidity data and controls varied areas in the home, sends data to the cloud via the Air724 IoT module via MQTT. To allow for a straightforward way of interaction with the system, the authors created an app that enables the control of various utilities in the home system, such as control, curtain control, fan control, and the data collected from the sensors.

3.2.7. Smart Services

In a smart city, the services component is one of the most important components to exist, having the ability to drastically change citizens’ lives by providing security and delivering citizens with their basic needs [6] (to name a few, clean water and sewer management).

Singh and Sharad [62] show one example of smart services worth noting: air quality monitoring, including the measurement of different parameters, carbon monoxide, sulphur dioxide, nitrogen dioxide, and ozone. The quality of air is being affected every day, and it is important to provide citizens with the healthiest paths to take. Multiple sensor nodes could be employed, allowing for a vast gathering of information on the status of air quality; the real-time data could be made available to citizens through mobile phones. Although it is not referred to, the preferred standard to be employed in this type of request for data gathering would be LoRa due to its low power consumption and the high coverage area achieved.

To enable smart management in industrial sewers, Gnanapriya P et al. [63] propose a cost-effective system that monitors sewage level, temperature, humidity, and gas sensors to monitor toxic gases in underground systems. Being a user-friendly platform, Arduino was chosen to be the mediator to send commands to receive data, send data to actuators, and display in the system. To enable Wi-Fi communication, an ESP8266 module is integrated to act as the access point and redirect data to the internet. This application provides a user-friendly interface, minimal maintenance, and financially feasible system.

Mohamed et al. [64] offer a solution for waste management: the integration of a smart trash bin enables the ability to verify trash levels in a bin via an ultrasonic sensor and to detect the presence of flammable gases with the use of a Metal Oxide Semiconductor (MQ)2-sensor. Providing a solution that optimises labour with the incorporation of a system that provides the optimised routes of trash bins that need to be cleared, workers’ labour can be optimised and reduced. The detection of flammable gases provides the option of alerting authorities, avoiding the dangers of a fire. To enable the communication of the sensor’s data, the authors use an ESP8266 module, which enables Wi-Fi communication.

3.2.8. Smart Health

Modani et al. [65] propose a voice-controlled smart health device capable of monitoring a patient’s blood pressure, body temperature, room temperature, and heart rate. The device is voice-controlled, which sends data in voice format to the doctor via a smartphone. The IoT solution is composed of a Node Microcontroller Unit (NodeMCU) ESP8266, which already has Wi-Fi capability. A heart-rate sensor capable of measuring the patient’s pulse, a pulse oximeter, and a heartbeat tracker sensor can measure heart rate and oxygen saturation. Finally, a body temperature sensor can be used to measure the patient’s temperature. The information collected is sent to an online open-source database used to store values in the cloud or Firebase. This would then send data into the application, allowing for healthcare staff to check important body vitals without having to physically move to check the patient’s health status.

The paper written by Thivyabrabha et al. [66] proposes an IoT solution capable of monitoring comatose patients, providing real-time alerts and improving patient care. The system offers eye blink monitoring, urinary level monitoring, temperature monitoring, finger movement monitoring, pulse, and heartbeat monitoring. The microcontroller used is a WeMOS D1 R2 UNO, which is based on the ESP8266 communication protocol over Wi-Fi. The information collected is previously sent to the Think Speak web app, which provides the data collected on the patient. The authors highlight that the system is aimed at improving monitoring solutions, with higher accuracy and reliability through the integration of sensors.

Al-Mahmud et al. [67] built a solution to help patients with their medication, reminding them when they need to take it. The authors suggest the creation of a box that reminds patients by emitting a sound and sending an alarm. The use of a servo motor enables the possibility of locking the box and only allows for the box to be opened when it is time to take medicine. The system is composed of a Wi-Fi module, which enables the system to send notifications to the user’s email address. The standard used to send the email is If This Then That (IFTTT), which enables email transfer to the patient’s mobile phone. Furthermore, the system is composed of an Arduino Uno and the ESP8266, which communicate via serial communication. The Arduino operates the management of the box via a DS3231 real-time clock (RTC) module, sending the alarm when there is an alarm time match with the RTC, triggering the buzzer, and an email will be sent to the patient’s phone, alerting the patient. Also, an LED on top of the medicine compartment will glow, and the medicine name will be displayed on an LCD. After the medicine is taken, the LED is turned off; if not taken, it will continue to glow, and the medicine name will be displayed in the LCD. To check information on patients and doctors, as well as medication and temperature data, a server was created to store and display this information on a website.

To provide a detailed overview of the existing standards and their use in the different domains of a smart city, these are shown in

Table 2. Summary of applications in smart cities.

Application Domain	Use Cases	Standards/Protocols Used	Relevant IEEE 1451 Sub-Standards
Smart agriculture	Soil monitorisation	Wi-Fi, HTTP, LoRa, UDP, TCP and Wi-Fi Hallow	IEEE 1451.0 IEEE 1451.5 IEEE 1451.5.5
	Automatic soil watering
Smart industry	Factory pollution monitorisation	UART and Wi-Fi	IEEE 1451.0 IEEE 1451.2 IEEE 1451.5
	Harbour crane weight monitorisation
Smart infrastructure	Geotechnical monitoring	NB-IoT, ESP-NOW, TCP/IP, 4G, Wi-Fi, Bluetooth, WAVE (IEEE 802.11p)	IEEE 1451.0 IEEE 1451.5 IEEE 1451.5.10
	Structural diagnostics
	V2V
Smart energy	Energy consumption monitorisation	SPI, Wi-Fi, I2C, UART and Radiofrequency	IEEE 1451.0 IEEE 1451.2 IEEE 1451.5
	Monitorisation of transformers
Smart transportation	Traffic control	LoRa, Wi-Fi, RFID and NFC	IEEE 1451.0 IEEE 1451.5 IEEE 1451.5.5 IEEE 1451.7
	smart bus system
	Parking lot space monitorisation
Smart building	Air quality monitorisation	Wi-Fi, MQTT, TCP/IP and HTTP	IEEE 1451.0 IEEE 1451.1.6 IEEE 1451.5
	Fire alarm system
	Energy saving
	Fall detection
	Earthquake detection
Smart services	Quality of air monitorisation	Wi-Fi	IEEE 1451.0 IEEE 1451.5
	Sewer monitorisation
	Waste monitorisation
Smart health	Health monitorisation	Wi-Fi	IEEE 1451.0 IEEE 1451.5
	Monitorisation of comatose patients
	Automated Medication Box

.

4. Fundamental Concepts of the IEEE 1451 Standard

4.1. IEEE 1451 Standard

The IEEE 1451 is a collection of sub-standards that creates a system of intelligent transducers, establishing interfaces that respect certain communication standards between transducers (actuators and sensors) and a transducer network interface [5]. The IEEE 21451 is the corresponding standard that is supported by the International Organisation for Standardisation (ISO) and the International Electrotechnical Commission (IEC). It is important to note that it is the same standard as IEEE 1451. Interoperability is only possible if an intelligent transducer complies with the standard. As well as having communication protocols, it must be able to provide certain functions, such as identifying itself, describing itself—i.e., describing the sensors/actuators it has—providing localisation, self-calibration, and data processing, and formatting the data obtained in a way that complies with the standard. Regarding these standards, it is possible to define the communication interface between transducers in a standardised way. There is the transducer device interface, which is the interface between a transducer device and a network device, and the interface between a network device and applications, which are further referred to and explained in more detail. This enables a standardised way to create interoperable systems in the areas of smart cities, smart buildings, smart homes, IoT, and IIoT. The standard is made up of ‘sub-standards’, which are shown in Figure 6. A relationship is formed between the various members of the family to enable the interoperability of the system itself. Some of the sub-standards shown in Figure 6 were adopted by the cooperative agreement ISO/IEC/IEEE.

The IEEE 1451 is a comprehensive set of sub-standards, the most relevant of which are IEEE 1451.0 [5], IEEE 1451.5 [68], ISO/IEC/IEEE 21451-1 [69], and ISO/IEC/IEEE 21451-002 [70]. These will be addressed later in Section 4.1, alongside the other sub-standards.

4.1.1. IEEE 1451 Standard and Its Main Components

The IEEE 1451 family of standards presents the concept of a network of intelligent transducers, and with this standard, it is possible to obtain a network that interconnects and allows for communication in a standardised way, which enables the interoperability of such a system and with other systems. The IEEE 1451 standard defines an architecture for intelligent transducers. In this architecture, there is a division of interfaces to allow for communication between the various parts of the system.

One of the communication interfaces lies between the network-capable application processor (NCAP) and the transducer interface module (TIM), which is performed through the transducer interface (TI) and between the NCAP and the network (or app), through the network interface (NI). It is not possible to have a TI without the presence of the TEDS. Thanks to the TEDS, when a transducer connects to the network, it can identify itself, display its capabilities, and communicate them to the system, sending them to NCAP. TEDS makes it possible to certify that different transducers can communicate with NCAP in a standardised way, improving automation and flexibility by allowing for plug-and-play operability.

Interoperability allows for communications with a network of sensors and actuators of several types, each one from a different manufacturer, even if they adopt different communication protocols (e.g., SPI, I²C, Wi-Fi, Bluetooth). There can be a common interface so that communication between them is possible, thus bridging the gap between the several types of communication. In this way, there would be no need to develop specific configurations for each device, allowing for manufacturers to create interoperable elements of a system without having to reconfigure them manually when a new device is added to the system. Figure 7 shows a reference model of the IEEE 1451 standard. To have interoperability, the IEEE 1451 standard divides a system into three main parts: the NCAP, the TIM, and the application (app).

As shown in Figure 7, the NCAP bridges the gap between the app and the TIM’s transducers (sensors/actuators), the NCAP is the network device that interfaces between the network and the transducer devices (TIM). Since the devices can be integrated into the system without manual reconfiguration, TEDS contains data on the transducers, describing their characteristics in an electronic datasheet that stores metadata about a specific transducer:

• Calibration data;
• Information about manufacturers;
• Range of measurements;
• Type of sensor or actuator;
• Communication protocol.

4.1.2. NCAP

The NCAP is the hardware and software that provides the link between the TIM and the app; it is responsible for being the middleware between the two [5]. Since each transducer sends data to an NCAP, the NCAP will process that data and send an organised packet of information back to the app. The NCAP ensures that all the data arrives in a standardised and easy-to-interpret form. It operates as a network node that allows for it to provide services such as reading a certain sensor or actuating a certain actuator and/or obtaining the TEDS of the transducers used.

4.1.3. TIM

A TIM is the physical interface that allows for communication between the sensors or actuators and the NCAP [5]. This interface allows for data to be collected from the sensors and commands to be sent to the actuators. It allows for sensors and actuators to connect to the network in a standardised way. Since the TIM interact directly with analogue signals coming from the transducers and are even sent to them, the TIM must be able to condition the signals in such a way that it is possible to make conversions from analogue to digital signals or from digital to analogue signals. This is possible using ADCs and DACs that are built into some of the TIMs’ inputs and outputs. For the NCAP to receive data from each transducer in a system, each TIM stores the technical data of its transducers (TEDS), which is then sent to NCAP on request.

4.1.4. Transducer Interface

To read the data collected by the sensors in a standardised way, receive the information from the respective TEDS of each TIM, and even actuate any actuator, an interface is used between NCAP and the TIM so that these actions respect the format of the standard. This interface can use any type of communication protocol, such as Bluetooth, Wi-Fi, or even Zigbee. Choosing a certain type of communication protocol means that the respective member of the standards family that uses the respective communication protocol will be used. So, the transducer interface is the interface responsible for establishing the connection between the NCAP and the TIMs [5].

4.1.5. Network Interface

Given the need to send commands to the NCAP, the user uses the app for this purpose. This connection between the NCAP and the app is made via the network interface, which, with an ethernet connection, can guarantee an uninterrupted and fast signal. Thanks to this interface, it is possible to send commands to obtain the TEDS, obtain data on the TIMs and data on the values read from the sensors, and even send a command to activate an actuator.

4.1.6. Transducer Channel

A transducer is a device that allows for the conversion of energy from diverse sources, with the function of converting energy from one domain (nature) into another. Through the conversion of physical signals into electrical signals, it is possible to measure these signals or even convert electrical signals into physical signals, allowing for actuation; this concept describes the principle of operation of actuators and sensors. In one transducer channel, it is possible to have data coming from or to one transducer that, in sequence, is captured by the respective TIM or sent by the TIM through the transducer channel to the respective transducer.

The transducer channel serves the purpose of being the gateway of its respective transducer and its TIM in a way that allows for a logical connection between the transducer channel and its physical connection. The mapping of this channel lets the TIM communicate the data of the transducer or to the transducer with the NCAP in a manner that means that the NCAP will not need to know what type of physical interface is used, allowing for data to be directly transferred between the NCAP to the transducer channel.

4.1.7. Transducer Channel Proxy

Knowing that data is communicated through NCAP and transducer channels and that information is gathered or communicated through a transducer, it would be useful to have a way of communicating data to a group of transducers, making it possible to have a network of multiple transducers connected to a single channel, allowing for the possibility of collecting multiple data in a single structure. This is achieved through a transducer channel proxy, which is a means to store the outputs of multiple sensors or input to multiple actuators in a single structure, but only represents a group of one type of transducers, meaning there cannot be a structure of both sensors and transducers in the same structure of data. Unlike a typical transducer channel, the transducer channel proxy does not have a transducer channel TEDS, calibration TEDS, transfer function TEDS, or frequency response TEDS, although the transducer channel proxies that exist in a TIM are defined in the meta-TEDS.

The manufacturer has the freedom to decide if the data that is received or sent to certain members of a proxy is rejected, with the receipt of one command that sets the respective transducer channel to command rejected. This allows for the commands or data to not be sent. There are two ways in which the transducer channel proxy can structure the datasets of the members of a proxy: these methods are known as block, which allows for datasets to be of different sizes; and interleave-only permits datasets to be the same size [5].

The interleave method stores data in an N-st data sample from transducer N, in contrast to the block method, which stores data in blocks of data in a fashion of a dataset from transducer N. To aid understanding, an example is shown in Figure 8.

4.1.8. TEDS

TEDS are datasheets in electronic format that store blocks of information relating to the required TEDS. There are four types of TEDS that all TIMs must have to comply with the standard. These are as follows:

• Meta-TEDS;
• Transducer Channel TEDS;
• Users Transducer Name TEDS;
• PHY TEDS.

Each TEDS stores a certain amount of information. The standard provides more TEDS, but these are optional, and it is not necessary for TIMs to display them, they just serve as a means of obtaining more information about the system itself. TEDS data is stored in ROM memory, although given that, in certain applications, this is not possible, there is the possibility of storing the information on the user’s system. For this purpose, a virtual TEDS is used, which, through the transducer channel, will transmit the TEDS. A Universal Unique Identifier (UUID) identifies each channel where the transducer for that channel will be connected and where the virtual TEDS will be stored and then sent to NCAP. A summary of all previously presented TEDS is provided in

Table 3. TEDS description and its function.

Type	TEDS	Characteristics
Mandatory	Meta	Describes how the TIM functions
	Transducer Channel	Detailed information about the transducer in a certain transducer channel
	Users Transducer Name	Stores the name of the transducer
	PHY	Describes the communication protocol used in the network interface and transducer interface
Optional	Calibration	Provides calibration constants to convert the outputs of the sensor into engineering units or convert a value of the engineering units into the form required by the actuator
	Frequency Response	Provides the frequency response of the transducer channel
	Transfer Function	Links series of individual transfer functions together to describe the frequency response of a transducer channel in algorithmic form
	Text-based	Provides text-based information about a TIM or transducer channel
	Commands	Text-based TEDS that allows for the manufacturer to define additional commands
	Identification	Provides data to identify a device or transducer channel within the system
	Geographic Location	Text-based TEDS that holds static geographic location information about TIMs
	Units extension	Text-based TEDS that provides the extension of SI units
	End User Application Specific	Block of memory for the users to store information
	Manufacturer-defined	Manufacturers can define TEDS that are not in the standard
	Security	Outlines the security protocols used in the IEEE 1451 network and transducer interfaces
	Time Synchronisation	Outlines time synchronisation protocols utilised in the IEEE 1451 network and transducer interfaces
	Energy	The item is still in process of being created

. This includes all TEDS shown previously, as well as those that are optional and were not presented [5].

4.1.9. IEEE 1451 Example System

An IEEE 1451 system has a multitude of potential applications. In this paper, the focus is on home automation. Sensors, actuators, security cameras, and microcontrollers are some of the systems that can be installed to provide automation within a household. Considering the requirements of a home automation system (comfort, security, energy efficiency, and convenience, to cite a few), it is evident that many physical quantities can be monitored. The monitoring of a home automation system is the collection of measurements of certain parameters, which have to be taken upon events that often require actuation. Accordingly, the installation of sensors and actuators is imperative for home automation and control. Following the collection of data by the sensors, it would be necessary to utilise TIM to collect the data from the sensors and send it to the NCAP. An ESP32 module would be a great fit for a TIM (however, others could be applicable). In this study, the ESP32 was chosen because of its potential to communicate using BLE (a model such as WROOM32D would be capable of this), which would be optimal for providing the system with the ability to communicate the data collected by the sensors, spending minimal energy. It can also use Wi-Fi, which allows for communication through multiple standards, thereby fostering interoperability and versatility throughout the system. The example described is illustrated in Figure 9.

In more detail, the standard creates a system where the NCAP can send commands to the TIMs. It allows the user to manually activate the motor or another actuator and not wait for the sensor to detect something and automatically control the shutters or another apparatus that is connected to the system. Figure 9 shows that the network interface (NI) establishes communication between the NCAP and the app, using an ethernet protocol to establish a fast connection with low latency between the app and the NCAP, allowing for commands to be sent to the NCAP by the app, such as requesting that the motor be activated, requesting the TEDS of certain transducers, or requesting that data sent from the NCAP to the app, such as data collected by the sensors that are connected to the respective TIMs, be transferred through a low-latency connection and for data transfer to be fast. This concludes with the creation of a responsive system.

Even though in an example shown in Figure 9, the standards used to transmit data between NCAP and TIMs are Bluetooth and Wi-Fi, and the transducer interface (TI) is not restricted to a sum list, and the standard allows for a variety of standards to establish communication between NCAP and TIM as long as the platform employed allows for the use of that standard. The communication medium used between NCAP and TIM can be wireless or wired. There are many standards that can be used in wired communication.

4.2. IEEE 1451 Collection of Sub-Standards

In

Table 4. Standard IEEE 1451 collection of sub-standards.

Sub-Standard	Definition
IEEE P1451.99	Defines the method that enables the data sharing and security of messages over transducer networks and other devices, providing an interoperable solution regardless of the type of communication used [71].
IEEE P1451.1.4	Defines a method for transporting IEEE 1451 messages over a network using the eXtensible Messaging and Presence Protocol.
IEEE P1451.1.5	Defines a method for transporting IEEE 1451 messages over a network using the Simple Network Management Protocol.
IEEE P1451.1.6	Defines a method for transporting IEEE 1451 messages over a network using MQTT [72].
IEEE 1451.0—2024	Establishes a framework for other sub-standards, defining their fundamental functions. Introduces the important TEDS concept and a standardised object responsible for interfacing transducer networks, characterising the function of NCAP [5].
IEEE 21451-1—2010	Defines an object model (NCAP) with a network interface for connecting processors to communication networks, sensors, and actuators, stipulating the services and components for the interactions [69].
IEEE P21451-002	Digital interface that defines the connection and communication between transducers and microprocessors. Also specifies the read and write logic to access TEDS [70].
IEEE 1451.2—1997	In charge of defining the transducer interface, stipulates wired communication between TIM and NCAP [73].
IEEE 1451.4—2004	NCAP provides an interface for processing analogue and digital signals. Defines a Mixed-Mode Interface [74].
IEEE 1451.5—2007	Addresses communication reliability and standards for wireless communication with transducers [68]. In this sub-standard exists its subvariants that define interfaces for LoRa [75], SigFox [76], and NB-IoT [77].
IEEE 1451.7—2010	Support for radio frequency identification (RFID) and defines the interface between RFID and transducers [78].

, a summary of the collection of IEEE 1451 sub-standards is presented.

5. Building Automation

5.1. Introduction to Building Automation

The adoption of automation provides convenience, comfort, and safety. Thus, the employment of automation in a manner that presents control over a system eases the barrier of use and integration. With the introduction of advanced communication technologies and advancements in IoT systems, the automation of building appliances is more accessible. The integration of wired and wireless networks of sensors and actuators in a house environment gives users the option to control and monitor building appliances in real-time [79]. Adding to actuation and data acquisition, smart buildings are also compromised by data processing, control, and communication.

Integrating an IoT system with these components creates an IoT application that establishes communication between electronic devices. With the establishment of this network, it is possible to have remote control over this smart network of electronic devices [79]. To enable the monitoring and control of the electronic devices, the data acquisition of sensors, and the actuators in the set system, there must be a central unit capable of managing data acquisition while also being able to send commands to control actuators and electronic devices that are part of the system. This central unit is a microcontroller and serves as the ‘brain’ of the IoT system, ensuring that all operations and communication between the components are integrated into the system [79,80]. Using a microcontroller ensures cost-efficiency, compact size, and the ability to handle complex tasks. This is key to guarantee that the cost of developing an IoT application for a smart building is reduced.

The microcontroller establishes data exchange between sensors, actuators, and user interfaces through both wired and wireless communication. The microcontroller has the capacity to process commands and data either in a local capacity or by way of transmission to a cloud-based server, thus ensuring that commands from the user are transmitted in such a manner as to help the desired actions. The enabling of both local and remote communication results in a unified smart network of electronic devices that is efficient, flexible, and user-friendly.

Some examples of building automation applications have already been shown in Section 3.2.6. An example that highlights the convenience of building automation systems is not needing to open or closing the blinds manually, as there are light sensors detecting when the sun is rising or coming down; intuitively, the lights in the building would automatically turn on/off in these events. With the deployment of sensor nodes that collect data on luminosity, the data collected is forwarded to other nodes that actuate the blinds according to the information received. Another example that was shown in [60] is the ability to save energy by implementing systems that allow for this in smart buildings. One example is the case of a vacant room; the lights in that room would remain off due to sensor nodes not detecting anyone, although in a case where it detects someone, the lights automatically turn on. If the lights were turned on automatically, this could save energy in instances where people forgot to turn off the lights or where there is no need for them to be on. An example of providing comfort would be to check the temperature via various sensor nodes, and, when a temperature change is necessary, it would be an opportunity to turn on the air conditioning system or another system capable of regulating temperature. In cases of cold temperatures, it would warm up the room, and in cases of high temperatures, it would cool the room. A building automation system is composed of sensors, actuators, and microcontrollers. However, due to the heterogeneity of IoT devices, it can be hard to integrate new devices into a system; the use of different devices in IoT applications can create friction in the scalability of systems and compatibility between devices, thus creating a need for a medium capable of allowing for the integration of different devices in IoT applications.

5.2. Enhancing Interoperability in Smart Buildings: The Role of IEEE 1451 Standard

With the intent of supporting the integration of new devices in a plug-and-play manner, the IEEE 1451 standard opts for providing an interface for devices from different manufacturers to communicate with each other, even while not using the same communication protocol. This solves the problem that proprietary communication frameworks face when lacking support for the integration of new devices from different manufacturers, while also enabling interoperability in a single system [81]. A system that complies with the IEEE 1451 standard provides users with a framework that promotes interoperability and flexibility. This is key to allowing for diversity in a building automation system, which also reduces the costs of the overall system, seeing that interoperability opens doors to the use of devices from different manufacturers, thus creating the opportunity for a diverse system that does not limit users’ applications. The IEEE 1451 standard presents a more composable architecture, allowing for the easier coordination of devices and the incrementation of new devices while providing a manufacturer-independent solution. Aiming for interoperability and flexibility in a way that allows the user to have easy control over the system, allowing for coordination across devices.

Showcasing the implementation of the IEEE 1451 standard in a smart building setting, Grisostomi et al.’s [82] research focuses on non-invasive wireless sensors used in an existing home environment to transform it into a smart home, proposing an application of modular wireless sensor nodes to create a smart environment. Placing sensor nodes everywhere in the house, the temperature, brightness, noise level, and humidity, as well as the electric power absorbed by the appliances, can be collected and analysed. The paper presents a novel modular design of a wireless sensor node. The node is composed of two main boards, related to the connection and the sensor interface, respectively, with the main purpose of this design being the standardisation of communication for the entire sensor network. Concerning the second application, the authors propose a smart home approach, designing an energy and comfort sensing board.

Figure 10 exemplifies how the IEEE 1451 standard bridges the lack of interoperability between devices, with an NCAP in the middle that bridges communications, allowing for devices that use different communication protocols to interact with each other. The NCAP establishes communication with all different devices, resulting in a system that is interconnected. Thus, information is sent across devices, even when there are different communication protocols at play. If each device follows the standard, interoperability between devices is established by the NCAP.

The impact of heterogeneity (IoT devices from different manufacturers and communication protocols that are not compatible) on the development of IoT systems is significant, affecting many crucial aspects of their employment and success. Primarily, the heterogeneity of devices poses a considerable challenge. IoT systems encompass a diverse array of devices, ranging from sensors to sophisticated actuators and smart devices. Each device owns distinct computing, storage, and energy capacities. This diversity poses significant challenges in the development of universally applicable software and firmware solutions, resulting in a need for the adoption of adaptable approaches tailored to each device type or the employment of complex abstraction layers.

Secondly, the absence of unified standards and the coexistence of multiple communication standards and data formats between different manufacturers and technologies leads to interoperability problems. The absence of seamless communication and interoperability among heterogeneous devices and systems hinders the efficacy and integration potential of IoT solutions, impeding the development of truly intelligent and collaborative systems.

Furthermore, heterogeneity extends to the communication protocols utilised. The necessity to support multiple protocols to communicate between divergent types of devices complicates the architecture of IoT systems, thereby increasing the complexity of developing gateways and middleware capable of translating and routing data between networks and devices with differing communication languages. The heterogeneity of data generated by diverse sensors and devices poses a significant challenge, data can vary in format, structure, frequency, and semantics, requiring complex processing and analysis to be integrated and used effectively by IoT applications.

The lack of standardisation in data formats makes it difficult to interpret and combine information from various sources. Finally, the heterogeneity of the hardware and software platforms on which IoT systems are built also introduces challenges. The diversity of operating systems, processing architectures, and development platforms makes it difficult to port and reuse solutions, as well as manage and update software across the entire IoT infrastructure.

In short, heterogeneity in IoT systems increases development complexity, hinders interoperability, raises increased security challenges, complicates scalability, and requires advanced solutions for data management and connectivity, significantly affecting the lifecycle and total cost of IoT projects. To mitigate these effects, interoperability standards, flexible architectures, adaptive middleware, and intelligent data management approaches are needed.

6. Conclusions

Heterogeneity is a fundamental challenge in the development of IoT systems, affecting every aspect of their design, deployment, and maintenance. Variations in device capabilities, communication protocols, data formats, and platforms complicates system integration, software development, and overall interoperability, leading to increased complexity, higher costs, and obstacles to scalability, security, and efficient data processing. To address these issues, there is a clear need for the usage of standardised protocols, flexible system architectures, adaptive middleware, and intelligent data management strategies to realise the full potential of IoT systems in a cohesive and sustainable manner.

The IEEE 1451 standard offers a robust solution to these challenges, creating a group of standards for smart transducers. The establishment of a common interface allows for the seamless communication between devices from different manufacturers, irrespective of their specifications. The IEEE 1451 standards offer a solution for plug-and-play integration; the TEDS allows for plug-and-play integration, ensuring the use of diverse devices, reducing system costs, and fostering interoperability. The flexibility and composability of IEEE 1451 enhance system scalability and adaptability, allowing for easy expansion and coordination. The use of an NCAP ensures seamless communication between devices, irrespective of their differing communication protocols, thereby fostering interoperability. This manufacturer-independent solution enhances system coherence and user control and eases the creation of diverse, cost-effective, and interoperable IoT systems, thereby addressing many of the challenges posed by heterogeneity in IoT environments.