J. Sens. Actuator Netw., Volume 9, Issue 2 (June 2020) – 14 articles

Data collection in an industrial environment enables several benefits: processes and machinery can be monitored; the performance can be optimized; and the machinery can be proactively maintained. To collect data from machines or production lines, numerous sensors are required, which necessitates a management system. The management of constrained IoT devices such as sensor nodes is extensively studied. However, the previous studies focused only on the remote software updating or configuration of sensor nodes. This paper presents a holistic Open Sensor Manager (OSEMA), which addresses also generating software for different sensor models based on the configuration. In addition, it offers a user-friendly web interface, as well as a REST API (Representational State Transfer Application Programming Interface) for the management. The manager is built with the Django web framework, and sensor nodes rely on ESP32-based microcontrollers. OSEMA enables secure remote software updates of sensor nodes via encryption and hash-based message authentication code. The collected data can be transmitted using the Hypertext Transfer Protocol (HTTP) and Message Queuing Telemetry Transport (MQTT). The use of OSEMA is demonstrated in an industrial domain with applications estimating the usage roughness of an overhead crane and tracking its location. OSEMA enables retrofitting different sensors to existing machinery and processes, allowing additional data collection. Full article

Information hovering is an information dissemination concept over a mobile set of peers which has not been investigated to the extent that other information dissemination paradigms have. It naturally appears in many vehicular network applications where information must be made available to vehicles within a confined geographical area for during some time period. One elementary strategy is to flood the area with data. Even in this case, some vehicles may never receive the content due to potential partitions created by low traffic density. In order to address this issue, in this work we propose a strategy based on epidemic routing in the hovering area, and probabilistic flooding outside it. Vehicles outside the hovering area serve as bridges towards partitions, leading to high reachability. We highlight the adaptive feature of the protocol, where the rebroadcast probability in partitions is adaptively regulated based on estimates of the density of vehicles in the hovering area. The performance of the proposed scheme is evaluated in VISSIM, using as the reference model in all simulation experiments a section of the road network in cities of Washington. The proposed protocol is shown to achieve the set design goals. Full article

The high cost of IEEE 802.11p-compliant devices and the lack of a widely adopted standard motivate the search for alternative methods for vehicular communication. As a consequence, and due to the ubiquity of smartphones, we see an increasing number of proposals based on Wi-Fi Direct, especially related to the integration of pedestrians in VANETs. Nevertheless, given the complexity of real experimentation, it is difficult to assess the ability of Wi-Fi Direct to offer connectivity in the vehicular environment on a large scale, leading to the evaluation through simulation. In order to verify the ability of a simulation model of reproducing the Wi-Fi Direct behavior, we analyze the performance of a safety application based on the communication range, packet delivery rate, and packet inter-reception time. In V2P scenarios, with and without line of sight, with varying vehicle speed, measurements using smartphones are performed and their results compared with those of OMNeT++ simulator. The results indicate, apart from the simulator’s accuracy, that the connection establishment time hinders the use of Wi-Fi Direct as a replacement to 802.11p. As an outcome of this observation, we evaluate a new transmission method for Wi-Fi Direct based on beacon stuffing, which mitigates the long connection establishment issue. Full article

A Bayesian framework is presented for finite element model-updating using experimental modal data. A novel likelihood formulation is proposed regarding the inclusion of the mode shapes, based on a probabilistic treatment of the MAC value between the model predicted and experimental mode shapes. The framework is demonstrated by performing model-updating for the Metsovo bridge using a reduced high-fidelity finite element model. Experimental modal identification methods are used in order to extract the modal characteristics of the bridge from ambient acceleration time histories obtained from field measurements exploiting a network of reference and roving sensors. The Transitional Markov Chain Monte Carlo algorithm is used to perform the model updating by drawing samples from the posterior distribution of the model parameters. The proposed framework yields reasonable uncertainty bounds for the model parameters, insensitive to the redundant information contained in the measured data due to closely spaced sensors. In contrast, conventional Bayesian formulations which use probabilistic models to characterize the components of the discrepancy vector between the measured and model-predicted mode shapes result in unrealistically thin uncertainty bounds for the model parameters for a large number of sensors. Full article

This paper presents a traffic light system based on wireless communication that provides a support infrastructure for intelligent control in the context of smart cities and aerotropolis areas. An aerotropolis is a metropolitan subregion with an infrastructure centered an airport. Traffic intensity is increasing all over the world. Intelligent dynamic traffic light system control is being sought to replace classic conventional manual and time-based systems. In this work, a wireless sensor network is designed and implemented to feed real-time data into an intelligent traffic light system control. A physical prototype is implemented for experimental validation outside the laboratory environment. The physical prototype shows robustness against unexpected issues and local failures. The results are positive in terms of the scope of experience gained, and there is potential for these tests to be extended to larger areas. Full article

Data integrity in wireless sensor networks (WSN) is very important because incorrect or missing values could result in the system making suboptimal or catastrophic decisions. Data imputation allows for a system to counteract the effect of data loss by substituting faulty or missing sensor values with system-defined virtual values. This paper proposes a virtual sensor system that uses multi-layer perceptrons (MLP) to impute sensor values in a WSN. The MLP was trained using a genetic algorithm which efficiently reached an optimal solution for each sensor node. The system was able to successfully identify and replace physical sensor nodes that were disconnected from the network with corresponding virtual sensors. The virtual sensors imputed values with very high accuracies when compared to the physical sensor values. Full article

Future 5G systems have set a goal to support mission-critical Vehicle-to-Everything (V2X) communications and they contribute to an important step towards connected and automated driving. To achieve this goal, the communication technologies should be designed based on a solid understanding of the new V2X applications and the related requirements and challenges. In this regard, we provide a description of the main V2X application categories and their representative use cases selected based on an analysis of the future needs of cooperative and automated driving. We also present a methodology on how to derive the network related requirements from the automotive specific requirements. The methodology can be used to analyze the key requirements of both existing and future V2X use cases. Full article

Cognitive radio (CR) technology is envisioned to use wireless spectrum opportunistically when the primary user (PU) is not using it. In cognitive radio ad-hoc networks (CRAHNs), the mobile users form a distributed multi-hop network using the unused spectrum. The qualities of the channels are different in different locations. When a user moves from one place to another, it needs to switch the channel to maintain the quality-of-service (QoS) required by different applications. The QoS of a channel depends on the amount of usage. A user can select the channels that meet the QoS requirement during its movement. In this paper, we study the mobility patterns of users, predict their next locations and probabilities to move there based on its history. We extract the mobility patterns from each user’s location history and match the recent trajectory with the patterns to find future locations. We construct a spectrum database using Wi-Fi access point location data and the free space path loss formula. We propose a machine learning-based mechanism to predict spectrum status of some missing locations in the spectrum database. We formulate a problem to select the current channel in order to minimize the total number of channel switches during a certain number of next moves of a user. We conduct an extensive simulation combining real and synthetic datasets to support our model. Full article

Road safety is an active area of research for the automotive industry, and certainly one of ongoing interest to governments around the world. The intelligent transportation system (ITS) is one of several viable solutions with which to improve road safety, where the communication medium (e.g., among vehicles and between vehicles and the other components in an ITS environment, such as roadside infrastructure) is typically wireless. A typical communication standard adopted by car manufacturers is IEEE 802.11p for communications. Thus, this paper presents an overview of IEEE 802.11p, with a particular focus on its adoption in an ITS setting. Specifically, we analyze both MAC and PHY layers in a dedicated short-range communication (DSRC) environment. Full article

Smart, secure and energy-efficient data collection (DC) processes are key to the realization of the full potentials of future Internet of Things (FIoT)-based systems. Currently, challenges in this domain have motivated research efforts towards providing cognitive solutions for IoT usage. One such solution, termed cognitive sensing (CS) describes the use of smart sensors to intelligently perceive inputs from the environment. Further, CS has been proposed for use in FIoT in order to facilitate smart, secure and energy-efficient data collection processes. In this article, we provide a survey of different Artificial Intelligence (AI)-based techniques used over the last decade to provide cognitive sensing solutions for different FIoT applications. We present some state-of-the-art approaches, potentials, and challenges of AI techniques for the identified solutions. This survey contributes to a better understanding of AI techniques deployed for cognitive sensing in FIoT as well as future research directions in this regard. Full article

The large spread of Distributed Energy Resources (DERs) and the related cyber-security issues introduce the need for monitoring. The proposed work focuses on an anomaly detection strategy based on the physical behavior of the industrial process. The algorithm extracts some measures of the physical parameters of the system and processes them with a neural network architecture called autoencoder in order to build a classifier making decisions about the behavior of the system and detecting possible cyber-attacks or faults. The results are quite promising for a practical application in real systems. Full article

Water covers a greater part of the Earth’s surface. However, little knowledge has been achieved regarding the underwater world as most parts of it remain unexplored. Oceans, including other water bodies, hold substantial natural resources and also the aquatic lives. These are mostly undiscovered and unknown due to the unsuited and hazardous underwater environments for the human. This inspires the unmanned exploration of these dicey environments. Neither unmanned exploration nor the distant real-time monitoring is possible without deploying Underwater Wireless Sensor Network (UWSN). Consequently, UWSN has drawn the interests of the researchers recently. This vast underwater world is possible to be monitored remotely from a distant location with much ease and less risk. The UWSN is required to be deployed over the volume of the water body to monitor and surveil. For vast water bodies like oceans, rivers and large lakes, data is collected from the different heights/depths of the water level which is then delivered to the surface sinks. Unlike terrestrial communication and radio waves, conventional mediums do not serve the purpose of underwater communication due to their high attenuation and low underwater-transmission range. Instead, an acoustic medium is able to transmit data in underwater more efficiently and reliably in comparison to other mediums. To transmit and relay the data reliably from the bottom of the sea to the sinks at the surface, multi-hop communication is utilized with different schemes. For seabed to surface sink communication, leading researchers proposed different routing protocols. The goal of these routing protocols is to make underwater communications more reliable, energy-efficient and delay efficient. This paper surveys the advancement of some of the routing protocols which eventually helps in finding the most efficient routing protocol and some recent applications for the UWSN. This work also summarizes the remaining challenging issues and the future trends of those considered routing protocols. This survey encourages further research efforts to improve the routing protocols of UWSN for enhanced underwater monitoring and exploration. Full article

Seismic behavior of tall buildings depends upon the dynamic characteristics of the structure, as well as the base soil properties. To consider these factors, the equations of motion for a multi-story 3D building are developed to include irregularity and soil–structure interaction (SSI). Inspired by swarm intelligence in nature, a new control method, known as swarm-based parallel control (SPC), is proposed in this study to improve the seismic performance and minimize the pounding hazards, by sharing response data among the adjacent buildings at each floor level, using a wireless-sensors network (WSN). The response of individual buildings is investigated under historic earthquake loads, and the efficiencies of each different control method are compared. To verify the effectiveness of the proposed method, the numerical example of a 15-story, 3D building is modeled, and the responses are mitigated, using semi-actively controlled magnetorheological (MR) dampers employing the proposed control algorithm and fuzzy logic control (FLC), as well as the passive-on/off methods. The main discussion of this paper is the efficiency of the proposed SPC over the independent FLC during an event where one building is damaged or uncontrolled, and an active control based upon the linear quadratic regulator (LQR) is considered for the purpose of having a benchmark ideal result. Results indicate that in case of failure in the control system, as well as the damage in the structural elements, the proposed method can sense the damage in the building, and update the control forces in the other adjacent buildings, using the modified FLC, so as to avoid pounding by minimizing the responses. Full article

V2I communications are characterized by the presence of network nodes in vehicles and in the infrastructures that these vehicles use, as well as by the wireless interactions among them. Safety-related applications demand stringent requirements in terms of latency and packet delivery probability, especially when safety messages have to be delivered to vehicles by the infrastructure. Interference issues stem from the typical characteristics of wireless communications, i.e., the noise of the wireless medium, the limited communication range of the wireless entities, and the receiver passivity of all the conventional wireless transceivers during transmissions. This paper presents a synchronization mechanism to artificially replicate at a host premises destructive interference due to hidden terminals, together with an application-level technique to minimize that interference by shifting the packet transmission time, similarly to the MAC TDMA channel access method. As both have been field-tested, the paper also analyzes the results of these tests, all performed with real hardware on IEEE 802.11p over different frequencies and transmission powers, and with repeatability in mind. The resulting figures attest that interference effects due to hidden terminals may indeed take place on real IEEE 802.11p networks, and that carefully designed time-shifting mechanisms can actively mitigate them. Full article