Search Results (116)

Air quality monitoring systems based on Internet of Things (IoT) technology are critical for addressing environmental and public health challenges, but their energy efficiency poses a significant challenge to their autonomous and scalable deployment. This study investigates strategies to enhance the energy efficiency of IoT-based air quality monitoring systems. A comprehensive analysis of sensor types, data transmission protocols, and system architectures was conducted, focusing on their energy consumption. An energy-efficient system was designed using the Smart Air sensor, Zigbee gateway, and Mini UPS, with its performance evaluated through daily energy consumption, backup operation time, and annual energy use. An integrated efficiency index (IEI) was introduced to compare sensor models based on functionality, energy efficiency, and cost. The proposed system achieves a daily energy consumption of 72 W·h, supports up to 10 h of autonomous operation during outages, and consumes 26.28 kW·h annually. The IEI analysis identified the Ajax LifeQuality as the most energy-efficient sensor, while Smart Air offers a cost-effective alternative with broader functionality. The proposed architecture and IEI provide a scalable and sustainable framework for IoT air quality monitoring, with potential applications in smart cities and residential settings. Future research should explore renewable energy integration and predictive energy management. Full article

The advancement of Internet of Things (IoT) technology has enabled battery-powered devices to be deployed across a wide range of applications; however, it also introduces challenges such as high energy consumption and security vulnerabilities. To address these issues, adiabatic logic circuits offer a promising solution for achieving energy efficiency and enhancing the security of IoT devices. Adiabatic logic circuits are well suited for energy harvesting systems, especially in applications such as sensor nodes, RFID tags, and other IoT implementations. In these systems, the harvested bipolar sinusoidal RF power is directly used as the power supply for the adiabatic logic circuit. However, adiabatic circuits require a peak detector to provide bulk biasing for pMOS transistors. To meet this requirement, a diode-connected MOS transistor-based voltage doubler circuit is used to convert the sinusoidal input into a usable DC signal. In this paper, we propose a novel adiabatic logic design that maintains low power consumption while optimizing energy and current fluctuations across various input transitions. By ensuring uniform and complementary current flow in each transition within the logic circuit’s functional blocks, the design reduces energy variation and enhances resistance against power analysis attacks. Evaluation under different clock frequencies and load capacitances demonstrates that the proposed adiabatic logic circuit exhibits lower fluctuation and improved security, particularly at load capacitances of 50 fF and 100 fF. The results show that the proposed circuit achieves lower power dissipation compared to conventional designs. As an application example, we implemented an ultrasonic transmitter circuit within a LoRaWAN network at the end-node sensor level, which serves as both a communication protocol and system architecture for long-range communication systems. Full article

This research presents an IoT-empowered adaptive mobility framework that integrates high-dimensional gesture recognition with edge-cloud orchestration for safety-critical human–machine interaction. The system architecture establishes a three-tier IoT network: a perception layer with 60 GHz FMCW radar and TOF infrared arrays (12-node mesh topology, 15 cm baseline spacing) for real-time motion tracking; an edge intelligence layer deploying a time-aware neural network via NVIDIA Jetson Nano to achieve up to 99.1% recognition accuracy with latency as low as 48 ms under optimal conditions (typical performance: 97.8% ± 1.4% accuracy, 68.7 ms ± 15.3 ms latency); and a federated cloud layer enabling distributed model synchronization across 32 edge nodes via LoRaWAN-optimized protocols (κ = 0.912 consensus). A reconfigurable chassis with three operational modes (standing, seated, balance) employs IoT-driven kinematic optimization for enhanced adaptability and user safety. Using both radar and infrared sensors together reduces false detections to 0.08% even under high-vibration conditions (80 km/h), while distributed learning across multiple devices maintains consistent accuracy (variance < 5%) in different environments. Experimental results demonstrate 93% reliability improvement over HMM baselines and 3.8% accuracy gain over state-of-the-art LSTM models, while achieving 33% faster inference (48.3 ms vs. 72.1 ms). The system maintains industrial-grade safety certification with energy-efficient computation. Bridging adaptive mechanics with edge intelligence, this research pioneers a sustainable IoT-edge paradigm for smart mobility, harmonizing real-time responsiveness, ecological sustainability, and scalable deployment in complex urban ecosystems. Full article

A LoRaWAN application architecture comprises three functional components: (i) nodes, which convert and wirelessly transmit data as LoRaWAN messages; (ii) gateways, which receive and forward these transmissions; and (iii) network servers, which process the received data for application delivery. The nodes convert data into LoRaWAN messages and transmit them wirelessly with the hope that one or more LoRaWAN gateway will receive the messages successfully. Then, the gateways pass on the received messages to a distant network server, where various processing steps occur before the messages are forwarded to the end application. If none of the gateways can receive the messages, then they will be lost. Although this default behaviour is suitable for some applications, there are others where ensuring messages are successfully delivered at a higher rate would be helpful. One such scenario is the application in this paper: monitoring maritime vessels and fishing equipment in offshore environments characterised by intermittent or absent shore connectivity. To address this challenge, the Custodian project was initiated to develop a maritime monitoring solution with enhanced connectivity capabilities. Two additional features are especially welcome in this scenario. The most important feature is the transmission of messages created in offshore areas to end users who are offshore, regardless of the unavailability of the ground network server. An example would be fishermen who are offshore and wish to position their fishing equipment, also offshore, based on location data transmitted from nodes via LoRaWAN, even when both entities are far away from the mainland. The second aspect concerns the potential use of gateway-to-gateway communications, through gateways on various ships, to transmit messages to the coast. This setup enables fishing gear and fishing vessels to be monitored from the coast, even in the absence of a direct connection. The functional constraints of conventional commercial gateways necessitated the conceptualisation and implementation of C-Mesh, a novel relay architecture that extends LoRaWAN functionality beyond standard protocol implementations. The C-Mesh integrates with the Custodian ecosystem, alongside C-Beacon and C-Point devices, while maintaining transparent compatibility with standard LoRaWAN infrastructure components through protocol-compliant gateway emulation. Thus, compatibility with both commercially available nodes and gateways and those already in deployment is guaranteed. We provide a comprehensive description of C-Mesh, describing its hardware architecture (communications, power, and self-monitoring abilities) and data processing ability (filtering duplicate messages, security, and encryption). Sea trials carried out on board a commercial fishing vessel in Sesimbra, Portugal, proved C-Mesh to be effective. Location messages derived from fishing gear left at sea were received by an end user aboard the fishing vessel, independently of the network server on land. Additionally, field tests demonstrated that a single C-Mesh deployment functioning as a signal repeater on a vessel with an antenna elevation of $15m$ above sea level achieved a quantifiable coverage extension of 13 km (representing a 20% increase in effective transmission range), demonstrating the capacity of C-Mesh to increase LoRaWAN’s coverage. Full article

The Internet of Military Things (IoMT) is transforming defense operations by enabling the seamless integration of sensors and actuators for the real-time transmission of critical data in diverse military environments. End devices (EDs) collect essential information, including troop locations, health metrics, equipment status, and environmental conditions, which are processed to enhance situational awareness and operational efficiency. In scenarios involving large-scale deployments across remote or austere regions, wired communication systems are often impractical and cost-prohibitive. Wireless sensor networks (WSNs) provide a cost-effective alternative, with Long-Range Wide Area Network (LoRaWAN) emerging as a leading protocol due to its extensive coverage, low energy consumption, and reliability. Existing LoRaWAN network simulation modules, such as those in ns-3, primarily support uniform periodic data transmissions, limiting their applicability in critical military and healthcare contexts that demand adaptive transmission rates, resource optimization, and prioritized data delivery. These limitations are particularly pronounced in healthcare monitoring, where frequent, high-rate data transmission is vital but can strain the network’s capacity. To address these challenges, we developed an enhanced sensor data sender application capable of simulating priority-based traffic within LoRaWAN, specifically targeting use cases like border security and healthcare monitoring. This study presents a priority-based data flow control protocol designed to optimize network performance under high-rate healthcare data conditions while maintaining overall system reliability. Simulation results demonstrate that the proposed protocol effectively mitigates performance bottlenecks, ensuring robust and energy-efficient communication in critical IoMT applications within austere environments. Full article

Research into, and the usage of, Low-Power Wide-Area Networks (LPWANs) has increased significantly to support the ever-expanding requirements set by IoT applications. Specifically, the usage of Long-Range Wide-Area Networks (LoRaWANs) has increased, due to the LPWAN’s robust physical layer, Long-Range (LoRa), modulation scheme, which enables scalable, low-power consumption, long-range communication to IoT devices. The LoRaWAN Medium Access Control (MAC) protocol is currently limited to only support single-hop communication. This limits the coverage of a single gateway and increases the power consumption of devices which are located at the edge of a gateway’s coverage range. There is currently no standardised and commercialised multi-hop LoRa-based network, and the field is experiencing ongoing research. In this work, we propose a complementary network to LoRaWAN, which integrates mesh networking. An ns-3 simulation model has been developed, and the proposed LoRaMesh network is simulated for a varying number of scenarios. This research focuses on the design decisions needed to design a LoRa-based mesh network which maintains the low-power consumption advantages that LoRaWAN offers while ensuring that data packets are routed successfully to the gateway. The results highlighted a significant increase in the packet delivery ratio in nodes located far from a centralised gateway in a dense network. Nodes located further than 5.8 km from a gateway’s packet delivery ratio were increased from an average of 40.2% to 73.78%. The findings in this article validate the concept of a mesh-type LPWAN network based on the LoRa physical layer and highlight the potential for future optimisation. Full article

Power transmission lines transfer energy between power plants and substations by means of a linear chain of towers. These towers are often situated over extensive distances, sometimes in regions that are difficult to access. Wireless sensor networks present a viable solution for monitoring these long chains of towers due to their wide coverage, ease of installation and cost-effectiveness. The proposed LoRaBUS approach implements and analyses the benefits of a linear topology using a mixture of LoRa and LoRaWAN protocols. This approach is designed to enable automatic detection of nearby nodes, optimise energy consumption and provide a prioritised transmission mode in emergency situations. On remote, hard-to-reach towers, a prototype fire protection system was implemented and tested. The results demonstrate that LoRaBUS creates a self-configurable linear topology which proves advantageous for installation processes, node maintenance and troubleshooting node failures. The discovery process collects data from a neighbourhood to construct the network and to save energy. The network’s autonomous configuration can be completed within approximately 2 min. In addition, energy consumption is effectively reduced 25% by dynamically adjusting the transmission power based on the detected channel quality and the distance to the nearest neighbour nodes. Full article

This paper presents an IoT-based monitoring system designed to measure energy exchanges within Renewable Energy Communities. The proposed system utilizes embedded devices functioning as IoT power meters, which communicate via LoRaWAN technology and employ the MQTT protocol. Members of the energy community can monitor energy flows in real time, enabling them to remain constantly informed about potential penalties and adopt behaviors that optimize incentives linked to the self-consumption of generated energy. Moreover, in the case of Renewable Energy Communities, incentive schemes can be adopted which allow exploiting the advantages of using storage units. In this context, it is important to correctly measure the energy terms which can be incentivized. This is not an easy task, especially when dealing with storage units for which the concept of negative energy input is used to identify the energy absorbed from the network to be fed back into the network when needed. This paper aims to propose the use of distributed power meters to identify the various energy contributions relevant for incentive calculations, such as negative energy input, produced and withdrawn energy, and self-consumed energy. A case study, involving some resources of a Renewable Energy Community, is presented, evidencing the advantages of the proposal. Full article

Smart grids are continuously evolving, incorporating modern technologies such as Wi-Fi, Zigbee, LoRaWAN or BLE. Wi-Fi are commonly used to transmit data from measurement systems, distribution control and monitoring systems, as well as network protection systems. However, since Wi-Fi networks primarily operate on unlicensed frequency bands, this introduces significant security risks for sensitive data transmission. In this paper, we propose a novel and highly efficient covert channels that utilize IEEE 802.11 Enhanced Distributed Channel Access (EDCA) for data transmission. It is also the first ever covert channel that employ three or four independent covert mechanisms to enhance operational efficiency. The proposed mechanism is also the first to exploit the Transmission Opportunity (TXOP) period and the access categories of the EDCA function. The protocol was developed and tested using the ns-3 simulator, achieving excellent performance results. Its efficiency remains consistent even under heavy network load with additional background traffic. These covert channels provide an innovative solution for securely transmitting large volumes of data within the smart grid. Full article

Fires and fire hazards in industrial environments pose a significant risk to safety, infrastructure, and the operational community. The need for real-time monitoring systems capable of detecting fires early and transmitting alerts promptly is crucial. This paper presents a fire monitoring system utilizing lightweight communication protocols, a multi-hop wireless network, and anomaly detection techniques. The system leverages Message Queue Telemetry Transport (MQTT) for efficient message exchange, the ESP-NOW for low-latency and reliable multi-hop wireless communications, and a radio environment map for optimal node placement, eliminating packet loss and ensuring robust data transmission. The proposed system addresses the limitations of traditional fire monitoring systems, providing flexibility, scalability, and robustness in detecting fire. Data collected by ESP32-CAM sensors, which are equipped with pre-trained YOLOv5-based fire detection modules, are processed and transmitted to a central monitoring server. Experimental results demonstrate a 100% success rate in fire detection transmissions, a significant reduction in latency to 150ms, and zero packet loss under REM-guided configuration. These findings validate the system’s suitability for real-time monitoring in high-risk industrial settings. Future work will focus on enhancing the anomaly detection model for greater accuracy, expanding scalability through additional communication protocols, like LoRaWAN, and incorporating adaptive algorithms for real-time network optimization. Full article

Today, agriculture faces many challenges, such as the use of inefficient methods that affect crop quality. Precision agriculture (PA), combined with advanced technologies, improves monitoring, while the integration of wireless communication optimizes processes and resources. This work presents the design of a communication prototype applied in precision agriculture, which allows the acquisition, processing, and wireless transmission of information extracted from the Cotonet pest to The Things Network (TTN) cloud server. This prototype integrates technologies and protocols such as LoRaWAN, Message Queuing Telemetry Transport (MQTT), Internet of Things (IoT) sensors, and Computer Vision. This prototype employs a robust processing and segmentation algorithm, which allows the recognition of pests in citrus plants based on color. The results show that lighting conditions, weather, and time of day influence the quality of the captured images. The relationship between image resolution, brightness, and processing time shows that higher-resolution images (1920 × 1080 pixels per image) provide better detection of pest pixels (greater than 50% of the pest index) but require longer processing time (28.415 ms on average). Furthermore, the developed system effectively detects an index of affection of Planococcus citri (Cotonet) in agricultural plantations through an end-to-end technological implementation that integrates image processing, wireless communication, and IoT technologies. Full article

Internet of Things (IoT) devices are ubiquitous in various applications, such as smart homes, asset and people tracking, and city management systems. However, their deployment in adverse conditions, including unstable internet connectivity and power sources, present new cybersecurity challenges through new attack vectors. The LoRaWAN protocol, with its open and distributed network architecture, has gained prominence as a leading LPWAN solution, presenting novel security challenges. This paper proposes the implementation of machine learning algorithms, specifically the K-Nearest Neighbours (KNN) algorithm, within an Intrusion Detection System (IDS) for LoRaWAN networks. Through behavioural analysis based on previously observed packet patterns, the system can detect potential intrusions that may disrupt critical tracking services. Initial simulated packet classification attained over 90% accuracy. By integrating the Suricata IDS and extending it through a custom toolset, sophisticated rule sets are incorporated to generate confidence metrics to classify packets as either presenting an abnormal or normal behaviour. The current work uses third-party multi-vendor sensor data obtained in the city of Lisbon for training and validating the models. The results show the efficacy of the proposed technique in evaluating received packets, logging relevant parameters in the database, and accurately identifying intrusions or expected device behaviours. We considered two use cases for evaluating our work: one with a more traditional approach where the devices and network are static, and another where we assume that both the devices and the network are mobile; for example, when we need to report data back from sensors on a rail infrastructure to a mobile LoRaWAN gateway onboard a train. Full article

The long-range wide area network (LoRaWAN) protocol is one of the most effective technologies for internet of things (IoT) applications, offering long-distance connectivity with low power consumption. This paper presents a practical approach by implementing a LoRa-based measurement prototype across urban and rural environments in the city of Quito, with the aim of assessing the performance and applicability of the technology in manifold settings. Specifically, we develop the required data collection and transmission code in the underlying network, ensuring smooth network integration. Furthermore, test environments are thoroughly characterized for numerical results, highlighting the conditions in the cities of Quito. The results obtained in both scenarios were satisfactory, allowing the comparison of the system’s performance in different contexts and providing key aspects of its practical applications and effectiveness. As the main contribution, empirical data were obtained to understand how long-range low-energy connectivity behaves, providing valuable information for comparing system performance in high-altitude cities above sea level, identifying practical applications, and optimizing its use in real IoT implementations. Full article

This study addresses an identified literature gap regarding indoor environmental quality in residential buildings, where the primary focus has traditionally been on energy performance rather than comfort optimization. Leveraging the low-cost and easy-to-implement LoRaWAN protocol, this research collects and analyses real-time data on comfort parameters, including temperature, CO₂ levels, humidity, lighting, atmospheric pressure, and total volatile organic compounds (TVOC) across various buildings within the INCUBE EU project. The results highlight the dynamic nature of the parameters and emphasize the importance of continuous monitoring to enhance comfort and energy efficiency in smart residential buildings. The findings advocate for integrating technologies like LoRaWAN to optimize indoor environmental quality, ultimately improving residential comfort and occupant well-being. Full article

This paper presents an efficient and secure method for updating firmware in IoT devices using LoRaWAN network resources and communication protocols. The proposed method involves dividing the firmware into fragments, storing them in the application server’s database, and transmitting them to remote IoT devices via downlink messages, without necessitating any changes to the device’s class. This approach can be replicated across any IoT LoRaWAN device, offering a robust and scalable solution for large-scale firmware updates while ensuring data security and integrity. The proposed method significantly reduces the downtime of IoT devices and enhances the energy efficiency of the update process. The method was validated by updating a block in the program memory, associated to a specific functionality of the IoT end device. The associated Intel Hex file was segmented into 17 LoRaWAN downlink frames with an average size of 46 bytes. Upon receiving the complete firmware update, the microcontroller employs self-programming techniques that restrict the update process to specific rows of the program memory, avoiding interruptions or reboots. The update process was successfully completed in 51.33 ms, resulting in a downtime of 16.88 ms. This method demonstrates improved energy efficiency compared to existing solutions while preserving the communication network’s capacity, making it an adequate solution for remote devices in LoRaWAN networks. Full article