Implementation Of Sensor Network Research Articles

RF-Powered Low-Energy Sensor Nodes for Predictive Maintenance in Electromagnetically Harsh Industrial Environments.

This work describes the design, implementation, and validation of a wireless sensor network for predictive maintenance and remote monitoring in metal-rich, electromagnetically harsh environments. Energy is provided wirelessly at 2.45 GHz employing a system of three co-located active antennas designed with a conformal shape such that it can power, on-demand, sensor nodes located in non-line-of-sight (NLOS) and difficult-to-reach positions. This allows for eliminating the periodic battery replacement of the customized sensor nodes, which are designed to be compact, low-power, and robust. A measurement campaign has been conducted in a real scenario, i.e., the engine compartment of a car, assuming the exploitation of the system in the automotive field. Our work demonstrates that a one radio-frequency (RF) source (illuminator) with a maximum effective isotropic radiated power (EIRP) of 27 dBm is capable of transferring the energy of 4.8 mJ required to fully charge the sensor node in less than 170 s, in the worst case of 112-cm distance between illuminator and node (NLOS). We also show how, in the worst case, the transferred power allows the node to operate every 60 s, where operation includes sampling accelerometer data for 1 s, extracting statistical information, transmitting a 20-byte payload, and receiving a 3-byte acknowledgment using the extremely robust Long Range (LoRa) communication technology. The energy requirement for an active cycle is between 1.45 and 1.65 mJ, while sleep mode current consumption is less than 150 nA, allowing for achieving the targeted battery-free operation with duty cycles as high as 1.7%.

Development of Lora P2P Network for Autonomous Seawater Quality Monitor for Green Powered Desalination Project

Scarcity of freshwater pushes countries impacted by climate change to investigate new sources of supply. Desalination plants powered by renewable energy can be the solution for a tropical developing country. Collection and treatment of seawater to produce freshwater generate an imbalanced water mass. In the case of a Reverse Osmosis Desalination Plant which pumps seawater to produce freshwater and brine as waste, the most important factor is the seawater quality, only available by observation. The design of a plant and its execution will depend on factors such as ambient temperature, salinity, and TDS. The main needs for a good multi-probe marine observation system are low energy consumption, simple monitoring, and coverage of a large area. For the sake of autonomy and ease of use, a functional and robust circuit can be set up using calibrated probes, micro-controllers, and small programmable boards. The use of programmable boards and connected probes are set up as network ‘nodes’ to send in-situ data measured from the water body. These nodes send the data using radio signal with LoRa protocol to a ‘gateway’ to store or transfer them. The parameters were measured at different time intervals, water depths, and distances from the coastline to observe how said factors affect the measurements. The results from the data collected are used to compare ocean modelling and satellite data. We present in this study the implementation of a long-range wireless autonomous sensor network and first validation tests in Jamaica and how it fills lack of information for a desalination project. Results indicate a good correlation between measure, modelling, and remote sensor. LoRa P2P network allows at an affordable price continuous monitoring of remote areas with great autonomy and resilience; results showed a successful transmission of > 80% within the network.

LoRa System for Monitoring and Facial Recognition

With the increasing tendency of incorporating technology into environments and activities in everyday life, new methods are being proposed to better integrate devices and mankind. Networks designed for monitoring areas through video and image systems are being implemented in several applications.Recent studies have shown interest from both the academy and industry to integrate wireless surveillance networks with low-cost and long range transmission technologies, such as LoRa (Long Range). With the intention to explore this topic, this work presents the development of a system prototype for intelligentmonitoring as a basis to future implementation of low-cost LoRa-based Wireless Image Sensor Networks (WISN). The system developed consists of a processing unit, a data routing interface and multiple sensor nodes. Its operation is autonomous and initiated through the detection of human presence, by the sensornode, capturing an image of the individuals present at each detection. The data is transmitted through LoRa devices to the central hub, where python-based methods of facial detection and recognition are employed. Several tests were performed to both adjust the system and to verify its efficiency. The results achievedwere satisfactory, indicating the viability of the proposed low-cost LoRa-based WISN.

A New Ammonium Smart Sensor with Interference Rejection.

In many water samples, it is important to determine the ammonium concentration in order to obtain an overall picture of the environmental impact of pollutants and human actions, as well as to detect the stage of eutrophization. Ion selective electrodes (ISEs) have been commonly utilized for this purpose, although the presence of interfering ions (potassium and sodium in the case of NH4+-ISE) represents a handicap in terms of the measurement quality. Furthermore, random malfunctions may give rise to incorrect measurements. Bearing all of that in mind, a smart ammonium sensor with enhanced features has been developed and tested in water samples, as demonstrated and commented on in detail following the presentation of the complete set of experimental measurements that have been successfully carried out. This has been achieved through the implementation of an expert system that supervises a set of ISEs in order to (a) avoid random failures and (b) reject interferences. Our approach may also be suitable for in-line monitoring of the water quality through the implementation of wireless sensor networks.

Design and implementation of wireless sensor network with LoRa technology for industrial monitoring

Design and implementation of wireless sensor network with LoRa technology for industrial monitoring

MACO-QCR: Multi-Objective ACO-Based QoS-Aware Cross-Layer Routing Protocols in WSN

Recent advances in microelectronics have encouraged the implementation of a wireless sensor network (WSN) in Intelligent Monitoring Systems (IMSs). The event data traffic in IMS applications requires timely and reliable delivery in order to react immediately with the appropriate actions. However, a sensor node's limited energy resource forces a trade-off to be made between delay and energy consumption while determining the route towards the BS. To cope up with the multi-constrained routing problem introduced by event data traffic in IMS, a multi-objective ant-colony-optimization based QoS-aware cross-layer routing (MACO-QCR) protocol has been proposed for inter-cluster communication in WSN-based IMS. The ACO algorithm is improved to be a multi-objective routing algorithm with considering the energy consumption cost and the end-to-end delay cost of a routing path as two optimization objectives, in which a routing path is produced through the multi pheromone information and the multi heuristic information consisting of two objective functions. To obtain Pareto optimal solutions, the MACO-ACO uses an external archive method based on fuzzy membership function to assign fitness values to the non-dominated solutions. Moreover, MACO-QCR adopts a cross layer approach that enables interaction between routing and medium access layer (MAC) layers for relay node selection. The simulation analysis shows that MACO-QCR has up to 10.5% and 6.8% more energy efficient, and has up to 19.1% and 25.3% less end-to-end delay compared to IAMQER and O_ARA protocols for a varying proportion of nodes having event data traffic in the network.

Efficient and high‐precision time synchronization for wireless monitoring of civil infrastructure subjected to sudden events

The implementation of a wireless smart sensor network (WSSN) to monitor a structure subjected to sudden events (e.g., earthquakes) poses many challenges. One typical challenge is to synchronize the data from different sensors during event-triggered sensing, because each wireless sensor has its own independent clock and their triggering time is generally different and unknowable. The challenge becomes more acute when real-time data acquisition is required to support vibration control or rapid damage assessment under sudden events. Although various strategies have been proposed to achieve synchronized sensing of WSSNs, all of these strategies fall short in addressing the challenges of sudden-event monitoring. In this paper, we first proposed an efficient two-stage time synchronization strategy for general structural health monitoring as a baseline and implemented it on a next-generation wireless smart sensor. Building upon the baseline method, efficient time synchronization strategies are proposed, which are fully autonomous and highly efficient for sudden-event monitoring. Two classes of events are considered: short-duration events, for example, bridge impacts, during which initial data loss issues are critical, and long-duration events, such as strong winds, which can benefit significantly from employing real-time monitoring. For short-duration events, a post-event time synchronization strategy is developed, which autonomously performs offline synchronization after measurement. For long-duration events, a real-time time synchronization strategy is proposed, which can support real-time applications under sudden events, for example, vibration control. These time synchronization strategies are experimentally validated to demonstrate the efficiency and accuracy (under 20-μs maximum error) of the proposed sudden-event synchronized sensing strategies.

Development of a low‐cost food color monitoring system

AbstractThe colorimetric analysis of food has gained much popularity in the last few decades. The present study reports the development of a low‐cost food color quality testing and process monitoring system. The proposed device consists of a hardware and a software (Color Magic) combination, which may allow the hardware to be used either for quality testing or process monitoring applications. In the quality‐testing mode, the software captures the image of the food products through the imaging system. Subsequently, the software processes the acquired image and computes color parameters in RGB (red, green, blue), CIELAB, and HSI (hue, saturation, intensity) color spaces. The software also synthesizes and displays the perceived color information in the display panel. The datalog of the sample color information can be sent to the user. Further, a separate software (Color Process), which is installed in a central server, was developed to implement a wireless star network topology for multi‐node process monitoring. The “Color Process” software allows users to acquire color information from multiple hardware. The software monitors the Hue from all the devices. It alerts the user via email if the Hue is beyond the range in any of the nodes. Finally, the device was tested for quality testing and process monitoring applications using colored placards and apple slices. The implementation of the wireless sensor network (WSN) in designing the multi‐node process monitoring makes the proposed device a unique system. This further would allow the device to be used for process monitoring at multiple remote locations.

Dynamic Buffer Sizing for Out-of-order Event Compensation for Time-sensitive Applications

Today’s sensor network implementations often comprise various types of nodes connected with different types of networks. These and various other aspects influence the delay of transmitting data and therefore of out-of-order data occurrences. This turns into a crucial problem in time-sensitive applications where data must be processed promptly and decisions must be reliable. In this article, we research dynamic buffer sizing algorithms for multiple, distributed, and independent sources, which reorder event streams, thus enabling subsequent time-sensitive applications to work correctly. To be able to evaluate such algorithms, we had to record datasets first. Five novel dynamic buffer sizing algorithms were implemented and compared to state-of-the-art approaches in this domain. The evaluation has shown that the use of a dynamic time-out buffering method is preferable over a static buffer. The higher the variation of the network or other influences in the environment, the more necessary it becomes to use an algorithm that dynamically adapts its buffer size. These algorithms are universally applicable, easy to integrate in existing architectures, and particularly interesting for time-sensitive applications. Dynamic time-out buffering is still a trade-off between reaction time and out-of-order event compensation.

Design and implementation of a low-cost sensor network to monitor environmental and agronomic variables in a plant factory

Monitoring equipment for plant-factory automation requires big capital investments. Low-cost open-source microcontroller platforms have been employed in agriculture to monitor and control different variables of importance for crop production. A low-cost plant-factory monitoring system for measuring air temperature, relative humidity, plant-leaf temperature, pH, electrical conductivity, dissolved oxygen and temperature of the nutrient solution is presented here. All the information is recorded in a micro SD memory and can be accessed by Bluetooth in real-time. The developed system was tested during a cycle of a lettuce crop in a research plant-factory facility. The quality of the collected data was evaluated and compared with a well-known research-grade monitoring system. The low-cost sensors showed an easy to correct bias when were compared to those of research-grade, with a correlation coefficient over 0.96. The results showed that low-cost systems, like the one implemented here, are a good alternative for monitoring environmental and physiological variables in controlled environmental agriculture facilities.

FPS‐MAC: Fuzzy priority scheduling‐based MAC protocol for intelligent monitoring systems

SummaryRecent advances in microelectronics have encouraged the implementation of a wireless sensor network (WSN) in intelligent monitoring systems (IMSs). The IMS for time‐critical applications requires timely and reliable data delivery without sacrificing the energy efficiency of the network. This paper proposes FPS‐MAC, a fuzzy priority scheduling‐based medium access control protocol, designed for event critical traffic in hierarchical WSN. The FPS‐MAC allows time‐critical event traffic to opportunistically steal the data slots allocated for periodic data traffic in event‐based situations. Additionally, a fuzzy logic‐based slot scheduling mechanism is introduced to provide guaranteed and timely medium access to emergency traffic load and ensures the quality‐of‐service (QoS) requirements of IMSs. Both analytical and simulation results for data throughput, energy consumption, and transmission delay of FPS‐MAC, TLHA, E‐BMA, and BMA‐RR have been analyzed to demonstrate the superiority of the proposed FPS‐MAC protocol.

Hierarchical Protocol Based on Recursive Clusters for Smart Parking Applications Using Internet of Things (IOT)

With the increasing number of vehicles, the management of parking spaces in cities is becoming increasingly important in improving the quality of life and combating air pollution. Indeed, finding a parking space at peak times and in congested areas of the population becomes a huge challenge for drivers. To remedy this problem, most modern cities have smart parking. The equipment of these smart parking is mainly based on the implementation of wireless sensor networks (WSN) to monitor, track, and collect real-time information on the occupancy status of each parking space. This information is then made available to drivers who are looking for an available parking space. However, sensor nodes have limitations in terms of energy and communication that affect the performance and quality of the wireless sensor network. Therefore, the design of a self-organization protocol for WSN that minimizes power consumption and maximizes the longevity of the WSN network must be taken into account when implementing and developing a sustainable and viable intelligent parking system. In this paper, we propose a protocol for self-organization of wireless sensor networks (WSN) for the management of parking spaces in outdoor and urban car parks. This protocol is based on building clusters using ZigBee transmission technology for multihop communication. Each sensor node will be installed in the ground of each parking space to monitor its availability by sending the empty or busy state of that space to the gateway using cluster head nodes (CHs). This approach has a robust and efficient self-organizing algorithm that minimizes energy dissipation and increases the lifetime of sensor nodes and the WSN network. The simulation results show that parking management systems in outdoor and urban car parks using the self-organization protocol presented are efficient and sustainable in terms of energy consumption, reliability of data transmission, and the longevity of the WSN network compared to other existing parking systems that use different self-organizing protocols for wireless sensor networks.

LoRa-Based Anomaly Detection Platform: Center and Sensor-Side

The implementation of a LoRa-based wireless sensor network, aiming to operate as an edge-based anomaly detection system is elaborated in this paper. The dominant prerequisites are defined as achieving a maximum possible sensing rate on edge, minimum Communication packet loss, the lowest possible false alarm, and the optimal resource management. In this regard, the developed sensor-side algorithm manages measurements accordingly to make effective communications with the center while transmitting either notification or requested compressed data packets. On the other side, a central algorithm keeps all the authorized sensors synchronized and updated. Besides, the center avoids network congestion primarily by queuing the received event notifications and later, by transmitting the data queries consecutively under supervision. The re-construction of the received anomaly-related data packets for further evaluations is another task to do by the center. Overall, the complementary proposal is experimentally tested and validated through the network operation in a worst-case scenario.

English

English

Gated Pipelined Folding ADC-Based Low Power Sensor for Large-Scale Radiometric Partial Discharge Monitoring

Partial discharge is a well-established metric for condition assessment of high-voltage plant equipment. Traditional techniques for partial discharge detection involve physical connection of sensors to the device under observation, limiting sensors to monitoring of individual apparatus, and therefore, limiting coverage. Wireless measurement provides an attractive low-cost alternative. The measurement of the radiometric signal propagated from a partial discharge source allows for multiple plant items to be observed by a single sensor, without any physical connection to the plant. Moreover, the implementation of a large-scale wireless sensor network for radiometric monitoring facilitates a simple approach to high voltage fault diagnostics. However, accurate measurement typically requires fast data conversion rates to ensure accurate measurement of faults. The use of high-speed conversion requires continuous high-power dissipation, degrading sensor efficiency and increasing cost and complexity. Thus, we propose a radiometric sensor which utilizes a gated, pipelined, sample-and-hold based folding analogue-to-digital converter structure that only samples when a signal is received, reducing the power consumption and increasing the efficiency of the sensor. A proof of concept circuit has been developed using discrete components to evaluate the performance and power consumption of the system.

Towards Safety Improvement of Measurement and Control Signals Transmission in Marine Environment.

This paper is dedicated to some aspects of maritime on-board safety improvement. The contribution of this article is a proposal to extend wireless communication on the ship, supported by examples of solutions that have not previously been used on board. Analyzed aspects concern the measurement and control signal transmission in hostile marine environment. A problem to solve is formulated, how to reduce a negative impact of this environment on effectiveness and reliability of maritime on board communication. The proposed ways for solving a problem under consideration cover recommendations concerning some aspects of ship construction and implementation of wireless sensor network. The main topic faced by the paper is concentrated on case study-based ZigBee as well as WiFi networks implementation in the area of the acquisition of data from sensors and measuring transducers connected to the terminal network. The exemplary implementation of ZigBee network, elaborated in Gdynia Maritime University is related, firstly, to the configuration of a simple wireless measurement and control channel, and secondly, to wireless communication channel supported by autonomously working microprocessor measurement and control system. WiFi networks were also tested in the same area of application. Finally, some concluding remarks are formulated.

Implementation of wireless sensor network for medical applications

There is an important requirement for additional cost-effective solutions for the supervision/monitoring of a patient’s tests during and after surgery or old patient as whenever the patient is at home or in the hospital. Advanced sensors combined with wireless communication can provide reduced expenses, improved observance, and higher life quality for the patient. In this paper, the Prototype will be developed for initial control of the basic vital functions of the patient’s body, whether patients of old age or even patients who are in hospital. This prototype is designed in a way to be effective and suitable for mobility because it is lightweight and can be carried by humans’ arm. Wireless communication using technology for 433 MHz through the product of HC-12 has many advantages including the distance up to 1000 meters as a wireless transmission range and several channels of 433.4 - 473 MHz, up to 100 communication channels. This prototype is developed, designed and tested with the primary version of a biomedical detector network for the long run wireless hospital and home care. The sensor network comprised of four completely different sensors and was tested in exceedingly hospital surroundings.

Design and Implementation of a Virtual Sensor Network for Smart Waste Water Monitoring.

Monitoring and analysis of open air basins is a critical task in waste water plant management. These tasks generally require sampling waters at several hard to access points, be it real time with multiparametric sensor probes, or retrieving water samples. Full automation of these processes would require deploying hundreds (if not thousands) of fixed sensors, unless the sensors can be translated. This work proposes the utilization of robotized unmanned aerial vehicle (UAV) platforms to work as a virtual high density sensor network, which could analyze in real time or capture samples depending on the robotic UAV equipment. To check the validity of the concept, an instance of the robotized UAV platform has been fully designed and implemented. A multi-agent system approach has been used (implemented over a Robot Operating System, ROS, middleware layer) to define a software architecture able to deal with the different problems, optimizing modularity of the software; in terms of hardware, the UAV platform has been designed and built, as a sample capturing probe. A description on the main features of the multi-agent system proposed, its architecture, and the behavior of several components is discussed. The experimental validation and performance evaluation of the system components has been performed independently for the sake of safety: autonomous flight performance has been tested on-site; the accuracy of the localization technologies deemed as deployable options has been evaluated in controlled flights; and the viability of the sample capture device designed and built has been experimentally tested.

Towards Industrial Ultra-Wideband Networks: Experiments for Machine Vibration Monitoring

We discuss the potential of ultra-wideband (UWB) technology for realizing use cases in industry 4.0 and demonstrate the implementation of an UWB sensor network with off-the-shelf transceivers for machine vibration monitoring. We propose a flexible medium access layer tailored for industrial sensing and show how the choice of its parameters is affected by the propagation environment and hardware constraints. Our real-world experiments reveal that links up to 20 meters can be achieved in industrial environments with an average packet loss rate in the order of 10 -6 for typical links. A comparison with a commercial vibration monitoring system based on IEEE 802.15.4 spread spectrum shows that UWB attains a twenty-times higher throughput for similar link ranges.

Implementation of Workshop Air Pollution Monitoring System Based On Wireless Sensor Network

Workshop contamination can lead to changes in the characteristics of the air. Welding process for example inside the workshop will generate different pollutants just like fume and gases. These gases may threat the environment. Also the direct exposure of these gases by people inside the workshop may be considered as a risk on their health. For all reasons mentioned above air pollution monitoring system is important issue to decrease the risk of low level of health. This paper introduces the implementation of wireless sensor network to monitor a workshop air pollution. The proposed system prototype contains a set of gas sensors (CO, H2, NH3, Butane, Propane, Ethanol and NO2) which are deployed on stack and infrastructure of Wireless sensor Network. These sensors are calibrated using appropriate calibration technologies. They are controlled by ARDUINO based microcontroller. Also there is the main server which Installed on raspberry pi 3 and contains the main database of the system which supports real time management strategies by using the web interface to monitor the air pollution in form of numbers and charts. Sensors which controlled by ARDUINO platform are connected to the server using the wireless technology (Wi-Fi) and the communication is done by using Message Queuing Telemetry Transport protocol (MQTT).When the level of Carbon Monoxide gas is above the threshold the system will send an alert email to the department of the civil defense. The system is checked and tested in the training workshops of University of Technology to measure the levels of harmful gases which may harm the people in the workshops.