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Underground mines are considered one of the riskiest facilities for human activities due to numerous accidents and geotechnical failures recorded worldwide over the last century, which have resulted in unsafe labor conditions, poor health outcomes, injuries, and fatalities. One significant cause of these accidents is the inadequate or nonexistent capacity for the real-time monitoring of safety conditions in underground mines. In this context, new emerging technologies linked to the Industry 4.0 paradigm, such as sensors, the Internet of Things (IoT), and LoRaWAN (Long Range Wide Area Network) wireless connectivity, are being implemented for planning the efficient, safe, and sustainable performance of underground mine labor environments. This paper studies the implementation of an ecosystem composed of IoT sensors and LoRa wireless connectivity in a data-acquisition system, which eliminates the need for expensive cabling and manual monitoring in mining operations. Laying cables in an underground mine necessitates cable support and protection against issues, such as machinery operations, vehicle movements, mine operator activities, and groundwater intrusion. As the underground mine expands, additional sensors typically require costly cable installations unless wireless connectivity is employed. The results of this review indicate that an IoT LoRaWAN-based wireless sensor network (WSN) provides real-time data under complex conditions, effectively transmitting data through physical barriers. This network presents an attractive low-cost solution with reliable, simple, scalable, secure, and competitive characteristics compared to cable installations and manually collected readings, which are more sporadic and prone to human error. Reliable data on the behavior of the underground mine enhances productivity by improving key performance indicators (KPIs), minimizing accident risks, and promoting sustainable environmental conditions for mine operators. Finally, the adoption of IoT sensors and LoRaWAN wireless connectivity technologies provides information of the underground mine in real-time, which supports better decisions by the mining industry managers, by ensuring compliance with safety regulations, improving the productive performance, and fostering a roadmap towards more environmentally friendly labor conditions. [ABSTRACT FROM AUTHOR]

Water is considered one of the vital natural resources and factors for performing short- and long-term agricultural practices on Earth. Meanwhile, globally, most of the available freshwater resources are utilized for irrigation purposes in agriculture. Currently, many world regions are facing extreme water shortage problems, which can worsen if not managed properly. In the literature, numerous methods and remedies are used to cope with the increasing global water crises. The use of precision irrigation water-saving systems (PISs) for efficient water management under climate change is one of them and is a highly recommended approach by researchers. It can mitigate the adverse effects of changing climate and help enhance water use efficiency, crop yield, and environmental footprints. Thus, the present study aimed to comprehensively examine and review PISs, focusing on their development, implementation, and positive impacts on sustainable water management. In addition, we searched the literature using different online search engines and reviewed and summarized the main results of the previously published papers on PISs. We discussed the traditional irrigation method and its modernization for enhancing water use efficiency, PIS monitoring and controlling, architecture, data sharing communication technologies, the role of artificial intelligence for irrigation water-saving, and the future prospects of the PIS. Based on the brief literature review, the present study concluded that the future of PISs seems bright, driven by the need for efficient irrigation water management systems, technological advancements, and increasing environmental awareness. As the water scarcity problem intensifies due to climate change and population growth, the PIS is poised to play a critical role in optimizing and modernizing water usage, increasing water use efficiency, and reducing environmental footprints, thus ensuring sustainable agriculture development. [ABSTRACT FROM AUTHOR]

In recent years, technological advancement characterized by heightened connectivity and digitization has revolutionized our interaction with the world. This evolution has been exemplified by the emergence of the Internet of Things, which has introduced a new era of digitization and automation, primarily propelled by devices based on the ESP32 microcontroller. This study seeks to comprehensively evaluate and characterize a fully functional sensor network built upon the ESP32 microcontroller. The evaluation covers three key aspects: network performance, the ESP32's built-in ADC peripheral, and the data acquisition system. The ESP32 device has demonstrated its capability to consistently sample sensors at a high rate with remarkable stability. The ESP32's built-in ADC exhibited undesirable behavior for analog devices, attributed to noise and non-linearity. As a result, in applications requiring precision with analog sensors, the utilization of a cost-effective external ADC, as employed in this study, is recommended. Finally, during the network analysis of the sensor network, no issues were identified. The data acquisition system exhibited no bottlenecks, and packet losses remained minimal, regardless of the sampling period. [ABSTRACT FROM AUTHOR]

Modern electromagnetic field (EMF) monitoring networks, such as the Serbian EMF RATEL network, are based on continuous EMF monitoring and offer daily observation of EMF levels in areas where people can reside for many hours a day and, consequently, experience an increased sensitivity to EMF exposure. Areas of particular importance are residential locations, kindergartens, schools, hospitals, and children’s playgrounds. Such areas require daily, comprehensive EMF monitoring and compliance checking with the prescribed reference levels. The whole process must be followed by transparent presentation of measurement results, to increase public confidence in the EMF monitoring. However, any additional information on EMF behavior, beyond elementary field strength measurements, is welcome. Therefore, this paper presents an innovative EMF data analysis of monitoring results, utilizing a time-averaging approach applied to acquired EMF data. The analysis is performed on a case study of EMF-sensitive areas in the Serbian city of Novi Sad, i.e., two kindergartens and an elementary school, revealing some of the concealed features in the behavior of the EMFs exposure in those areas, through a comparative evaluation.

Water is considered one of the vital natural resources and factors for performing short- and long-term agricultural practices on Earth. Meanwhile, globally, most of the available freshwater resources are utilized for irrigation purposes in agriculture. Currently, many world regions are facing extreme water shortage problems, which can worsen if not managed properly. In the literature, numerous methods and remedies are used to cope with the increasing global water crises. The use of precision irrigation water-saving systems (PISs) for efficient water management under climate change is one of them and is a highly recommended approach by researchers. It can mitigate the adverse effects of changing climate and help enhance water use efficiency, crop yield, and environmental footprints. Thus, the present study aimed to comprehensively examine and review PISs, focusing on their development, implementation, and positive impacts on sustainable water management. In addition, we searched the literature using different online search engines and reviewed and summarized the main results of the previously published papers on PISs. We discussed the traditional irrigation method and its modernization for enhancing water use efficiency, PIS monitoring and controlling, architecture, data sharing communication technologies, the role of artificial intelligence for irrigation water-saving, and the future prospects of the PIS. Based on the brief literature review, the present study concluded that the future of PISs seems bright, driven by the need for efficient irrigation water management systems, technological advancements, and increasing environmental awareness. As the water scarcity problem intensifies due to climate change and population growth, the PIS is poised to play a critical role in optimizing and modernizing water usage, increasing water use efficiency, and reducing environmental footprints, thus ensuring sustainable agriculture development.

The term "smart agriculture" refers to a management concept that is centered on industrial agriculture. It makes use of cutting-edge technologies such as big data, cloud, and the Internet of Things to monitor, automate, and evaluate agricultural operations. Smart agriculture is a management concept. Software and sensors are used in smart agriculture, also known as precision agriculture. Smart agriculture is managed by the software. This pa-per proposes the development of low-cost environment parameters and electrical quantities monitoring device. According to the findings, such Internet of Things devices are suited for digitizing the relevant data in order to ac-quire information that may help farmers make optimal changes. [ABSTRACT FROM AUTHOR]

Wireless Sensors Networks are integrating human daily life at a fast rate. Applications cover a wide range of fields, including home security, agriculture, climate change, fire prevention, and so on and so forth. If WSN were initially flat networks, hierarchical, or cluster-based networks have been introduced in order to achieve a better performance in terms of energy efficiency, topology management, delay minimization, load balancing, routing techniques, etc. As cluster-based algorithms proved to be efficient in terms of energy balancing, security has been of less importance in the field. Data shared by nodes in a WSN can be very sensitive depending on the field of application. Therefore, it is important to ensure security at various levels of WSN. This paper proposes a formal modeling of the energy consumed to secure communications in a cluster-based WSN in general. The concept is implemented using the Proof of Authentication (POAh) paradigm of blockchain and applied to a Multi-hop Clustering Algorithm based on spectral classification. The studied metrics are residual energy in the network, the number of alive nodes, first and last dead node. [ABSTRACT FROM AUTHOR]

Localization is a crucial concern in many Wireless Sensor Network (WSN) applications. Moreover, getting accurate information about geographic positions of nodes (sensors) is very interesting to make the collected data useful and meaningful. The based connectivity algorithms aim to localize multi-hop WSN thanks to their advantages such as their simplicity and acceptable accuracy. However, the localization accuracy may be relatively low due to environment conditions. An Extreme Learning Machine technique (ELM) is given in this manuscript to minimize the localization error in Range-Free WSN. In this work, based on the Cascade-ELM, we propose a Cascade Extreme Learning Machine (Cascade-ELM) to improve the localization accuracy in Range-Free WSN. We applied the proposed methods in different scenarios of Multi-hop WSN. In our study, we focused on an isotropic and irregular environment. Simulation results prove that the proposed Cascade- ELM algorithm greatly optimizes the localization accuracy in comparison with other algorithms issued from smart computing techniques. Improved localization performances, when compared to previous works, are obtained for isotropic environments. [ABSTRACT FROM AUTHOR]

Nowadays, using mobile computing devices and the Internet of Things (IoT) in networks have posed several challenges to match up the forthcoming technological requirements. Wireless Sensors Network (WSN) is considered as an important component of the IoT which produces a massive amount of data (big data). However, dealing with limited capacities of the elementary components of a network in an IoT enabled WSN, is a key challenge. The existing approaches in the literature are inadequate for large networks and cannot be applied to IoT platform without adaptation. Data Centric Network (DCN) is an important notion for the future Internet architecture to resolve the problems related to big data manipulation. In fact, using a DCN strategy for the resource limited capacities WSN enabled IoT networks is beneficial to manage densely deployed and mobile components to enhance the data gathering mechanism. In this context, this paper proposes an IoT cluster based routing protocol for data centric mobile wireless sensors networks named ICMWSN. The proposed algorithm fits with a WSN belonging a large number of mobile sensors as well as a mobile sink. It is based on a clustering technique to form multi-hops clusters around fixed pre-elected CHs. Besides, an effective tour construction method is involved for the mobile sink to collect data from the eventual cluster heads. The extensive simulation results proved that ICMWSN outperformed the compared methods in terms of energy consumption, network lifetime and data delivery rate. [ABSTRACT FROM AUTHOR]

In this paper we present a blockchain based system for the supply chain management of a particular Italian bread. Goal of the system is to guarantee a transparent and auditable traceability of the Carasau bread where each actor of the supply chain can verify the quality of the products and the conformity to the normative about the hygienic-sanitary conditions along the chain. To realize this system we relied on the Blockchain and the Internet of Thing technologies in order to provide a trustless environment, in which trust is placed in cryptography, in mathematical operations and on the network, and not in public or private companies. Thanks to the use of digital technologies the system aims to reduce the data entry errors and the risk of tampering. Our system is designed so that along the supply chain, the nodes equipped with several sensors directly communicate their data to Raspberry Pi units that elaborate and transmit them to Interplanetary File System and to the Ethereum Blockchain. Furthermore, we designed ad hoc Radio Frequency Identification and Near Field communication tags to shortly supply the proposed system with information about the products and batches. The dedicated RFID tags robustness during on-bread operation was numerically tested. The system will easily allow end consumers to have a transparent view on the whole journey from raw material to purchased final product and a supervisory authority to perform online inspections on the products’ quality and on the good working practices.

The main concern of this research is to control traffic flow and monitor highways by installing wireless sensors. Therefore, a new multi-objective model is proposed to find the optimal location of wireless sensors along highways. The sensors are paired and each pair of sensors communicates and interacts with each other to receive information from passing cars. The speed estimation of the vehicles passing through this pair of sensors must have the minimum deviation from the actual speed that is obtained by an accurate measurement. This deviation is called measurement error, which is minimized in the first objective function. In this research when traffic jams happens, some sensors located in proper distance with enough energy, move into the traffic area to reduce the measurement error which is caused by traffic congestion. In fact, for each traffic area a new location problem should be solved to relocate sensors so that the maximum decrease in error rate happens. The second objective maximizes the error reduction resulted from sensors movement. In this paper, movement of sensors is considered based on the amount of solar energy stored in the sensor at that moment. Finally, the third objective function maximizes the benefits resulted from detecting the bottlenecks in highways. Since some parameters of the objective functions such as error rates, error reduction resulted from movement of sensors and benefits are uncertain, this research employs a multi-objective robust optimization approach which results in a traffic control plan which is less sensitive to the realization of uncertain parameters.

A Wireless Sensor Network typically uses a large number of power‐constrained sensor nodes for sensing phenomenal data and for its processing. The lifetime of a sensor node is limited and this is a great challenge for researchers to sustain the network for a long time. Since, the data transmission from a sensor node to the base station is more power consuming, the hierarchical routing protocols play a major role in multihop communication and to prolong the network life time. It uses a clustering approach with an overhead of cluster head (CH) selection to attain this. This overhead needs proper addressing and to be reduced by some means. The work in this paper employs a new approach based on low‐energy adaptive clustering hierarchy (LEACH) and considers network load for electing CH in addition to number of links, residual sensor energy and distance. Here, energy and time are used for calculating load on a CH. The simulation results show that the proposed protocol performs better than LEACH, LEACH‐I, and NR‐LEACH algorithms on the parameters of average energy ratio throughput, end‐to‐end delay, packet delivery ratio, and a number of alive nodes. [ABSTRACT FROM AUTHOR]

Relative pose estimation refers to estimate the relative attitude and translation between multiple platforms. For mobile platforms, tracking the relative pose with pairwise range is challenging for highly nonlinear associations between measurement and state. This article proposes a promising framework using pairwise range to estimate the relative pose parameterized with Lie algebra. It is compatible with the existing Gauss-Newton method and the Levenberg-Marquardt method. We analyze the existence of the optimal solution based on the rank of the Hessian matrix, which turns into a discussion of sensors placement. The associated unconstrained Cramer-Rao Lower Bound with fewer variables is presented. To track moving platforms, we derived a novel and accurate relative kinematics without angular accelerations. An extended Kalman filter incorporating the measurement of an IMU is designed to generate smooth poses. A simplified version of the optimizer with less dimension is introduced to the application of aerobridge, which is also compatible with other multilink devices. Simulations verify the proposed algorithm and the comparisons with the existing popular methods prove its novelty.

This article deals with the creation of a power supply system of wireless sensors which take measurements and transmit data at time intervals, the duration of which is considerably less than the activation period of sensors. The specific feature of the power supply system is the combined use of devices based on various physical phenomena. Electrical energy is generated by thermoelectrochemical cells. The temperature gradient on the sides of these cells is created by a vortex tube. A special boost DC/DC converter provides an increase in the output voltage of thermoelectrochemical cells up to the voltage that is necessary to power electronic devices. A supercapacitor is used to store energy in the time intervals between sensor activation. A study of an experimental sample of the power supply system for wireless sensors was conducted. Using the model in MATLAB + Simulink program, the possibility and conditions for creating the considered system for a particular type of wireless sensor were shown.

Wireless sensor networks (WSNs) have attracted a lot of interests over last years in security to ensure integrity, authenticity and data confidentiality. WSN applications are numerous, which range from smart home in indoor deployment offices to smart agriculture in outdoor deployments. Due to the deployment of nodes in remote areas, the solution brought to the wireless sensor network to increase the information security consists in protecting the messages exchanged between nodes. In the paper, modifications in the key management scheme are presented. Due to resource constraints in the sensor nodes, the proposed scheme ensures a distribution of the secured keys between nodes. New session keys transmitted between sensor nodes are defined during the discovery and path key phases. The experimental results prove that the proposed scheme is adapted to the WSN applications in terms of connectivity and resiliency. [ABSTRACT FROM AUTHOR]

This article will present a simple technical solution for a low-power and real-time air quality monitoring system. The whole package of software and hardware technical solutions applied for recording, transmitting and analyzing data is briefly described. This original monitoring system integrates a single chip microcon-troller, several dedicated air pollution surveillance sensors (for PM10, PM2.5, SO2, NO2, CO, O3, VOC, CO2), a LoRaWAN communication module and an online platform. This system was tested and applied under real field conditions. Depending on the measured values, it provides alerts, or, it can lead to the re-placement of specific components in the exhaust equipment. This article will pre-sent some experimental results, validated also by official measurements of government operated air quality stations. [ABSTRACT FROM AUTHOR]

The Minimum-Cost Bounded-Error Calibration Tree problem (MBCT) is a wireless network optimization problem that arises from the sensors' need of periodical calibration. The MBCT takes into account two objectives. The first is to minimize the communication distance between the network sensors, while the second is to reduce the maximum post-calibration error in the network. In this paper, we propose a mathematical formulation for the MBCT. Furthermore, we solve the problem using two different implementations of an Augmented ϵ -Constraint Method ( a u g ϵ - C M ) that incorporate the proposed formulation. We also employed the Pareto-fronts obtained by a u g ϵ - C M to evaluate the Node-depth Phylogenetic-based Non-dominated Sorting Artificial Immune System (NPE-NSAIS), the most recent heuristic in the literature for MBCT. Computational experiments showed that a u g ϵ - C M can solve MBCT instances up to 50 nodes. Furthermore, a statistical test demonstrated that the running times of one of the a u g ϵ - C M implementations was significantly smaller than those of the other. Finally, we show that NPE-NSAIS solutions are very close to the Pareto-fronts given by a u g ϵ - C M , achieving good results on the evaluated metrics. [ABSTRACT FROM AUTHOR]

Wireless sensor network (WSN) has become one of the most important technologies because of its reliable remote monitoring ability. As sensors are often deployed at remote and/or hazardous environments, it is important to be able to perform faulty sensor nodes self-diagnosing. In this paper, we formulate WSN faulty nodes identification as a pattern classification problem. This paper uses semi-supervised method for faulty sensor nodes classification. To enhance the learning performance, we also introduce a label propagation mechanism which is based on local kernel density estimation. The basic concept of the method is to estimate the posterior probability of a scene that belongs to normal or different faulty modes. In this paper, we implemented a software platform to study WSN under different number of sensor nodes and faulty conditions. Our experimental results show the proposed semi-supervised method is highly effective. Thorough comparative analyses with other state-of-art semi-supervised learning methods were included. The obtained results confirmed that our proposed algorithm can deliver improved classification performance for WSN. [ABSTRACT FROM AUTHOR]

• Perpetual awareness systems are sensing systems characterized by continuous monitoring and ubiquitous sensing; they are essential to many safety and mission-critical applications, e.g. assisted living, healthcare and public safety. • The SAFER system for assisted living, uniquely leverages context information (e.g. activities of daily living 'ADLs', location) for energy-optimized sensor activations to detect anomalous events, such as falls. • Experimental studies with real world datasets indicated that the proposed technique was able to achieve more than 80% reduction in energy consumption, in a heterogeneous IoT platform for fall detection, thereby doubling the system-lifetime without loss of sensing accuracy. The IoT revolution has provided a promising opportunity to build powerful perpetual awareness systems. Perpetual awareness systems are sensing systems characterized by continuous monitoring and ubiquitous sensing; they are essential to many safety and mission-critical applications, e.g. assisted living, healthcare and public safety. In this paper, we present SAFER, a perpetual heterogeneous IoT system; deployed in homes to detect critical events (injury, hazardous-environment) that must trigger immediate action and response. A key challenge here is the energy consumption associated with perpetual operations. We propose a novel energy-aware perpetual home IoT system where battery-operated and wall-powered IoT devices co-execute to ensure safety of occupants. We use a semantic approach that utilizes context of extracted activities of daily living (ADLs) from device data to drive energy optimized sensor activations. To validate our approach, we developed an elderly fall detection system using multi-personal and in-situ sensing devices derived from real world deployments in SCALE project which has been deployed in Montgomery county, MD. Using initial measurements to drive larger simulations, we show that proposed Cost-Function-Gradient algorithm can achieve greater than 4X reductions in energy dissipation and doubling system of battery powered devices lifetime without loss of sensing accuracy. [ABSTRACT FROM AUTHOR]

Location-based services have increased in popularity in recent years and can be fruitfully exploited in the field of smart homes, opening the doors to a wide range of personalized services. In this context, radio technology can be widely employed since, other than connecting devices in the home system, it offers solutions for the user localization issue without the need of any extra device. Techniques based on received signal strength indicator (RSSI) are often used, relying on fingerprinting or proximity algorithms. In this paper, a novel RSSI-based fingerprinting approach for room-level localization is presented: it is a threshold algorithm based on receiver operating characteristic analysis. Moreover, the actual user location is estimated from his/her interaction with the home system devices deployed in the house: if the home environment is inhabited by more than one person, it becomes of utmost importance the identification of who is actually interacting with a given device. A proximity method is exploited for this purpose. Tests have been carried out to characterize the approach, particularly, the effects of RSSI samples, number and position, of the anchor nodes have been analyzed. Finally, some considerations about power consumption of the mobile node have been presented. [ABSTRACT FROM AUTHOR]

A Wireless Sensor Networks (WSNs) consists basically of a group of nodes, that communicate with each other through a wireless transmission, and does not need any existing infrastructure. The recent developments in technology and wireless communication, to be used in various applications, foster the development of Wireless Body Area Networks (WBANs). They are emerging as important networks in order to reduce the need for patients, and to help the elderly and chronically ill people to live an independent life. In this paper, we propose a routing protocol for wireless body area networks, to transfer data in the network with minimum energy consumption, and longer network lifetime through multi-hop communication. The proposed protocol has been verified by performing simulations, and the obtained results show that our routing protocol ensures a robust optimisation of the energy consumption which helps to increase the lifetime of the network and its stability. [ABSTRACT FROM AUTHOR]

Residual motion of upper limbs in individuals who experienced cervical spinal cord injury (CSCI) is vital to achieve functional independence. Several interventions were developed to restore shoulder range of motion (ROM) in CSCI patients. However, shoulder ROM assessment in clinical practice is commonly limited to use of a simple goniometer. Conventional goniometric measurements are operator-dependent and require significant time and effort. Therefore, innovative technology for supporting medical personnel in objectively and reliably measuring the efficacy of treatments for shoulder ROM in CSCI patients would be extremely desirable. This study evaluated the validity of a customized wireless wearable sensors (Inertial Measurement Units—IMUs) system for shoulder ROM assessment in CSCI patients in clinical setting. Eight CSCI patients and eight healthy controls performed four shoulder movements (forward flexion, abduction, and internal and external rotation) with dominant arm. Every movement was evaluated with a goniometer by different testers and with the IMU system at the same time. Validity was evaluated by comparing IMUs and goniometer measurements using Intraclass Correlation Coefficient (ICC) and Limits of Agreement (LOA). inter-tester reliability of IMUs and goniometer measurements was also investigated. Preliminary results provide essential information on the accuracy of the proposed wireless wearable sensors system in acquiring objective measurements of the shoulder movements in CSCI patients.