Sensor Node For Detection Research Articles

Deployment of an IoT based sensor node for faults detection and classification in electrical secondary distribution networks

Deployment of an IoT based sensor node for faults detection and classification in electrical secondary distribution networks

Intrusion Detection Mechanism for Empowered Intruders Using IDEI

In the past, intrusion detection has been extensively investigated as a means of ensuring the security of wireless sensor networks. Anti-recon technology has made it possible for an attacker to get knowledge about the detecting nodes and plot a route around them in order to evade detection. An "empowered intruder" is one who poses new threats to current intrusion detection technologies. Furthermore, the intended impact of detection may not be obtained in certain subareas owing to gaps in coverage caused by the initial deployment of detection nodes at random. A vehicle collaboration sensing network model is proposed to solve these difficulties, in which mobile sensing cars and static sensor nodes work together to identify intrusions by empowered intruders. An algorithm for mobile sensing vehicles, called Intrusion Detection Mechanism for Empowered Intruders(IDEI), and a sleep-scheduling technique for static nodes form the basis of our proposal. Sophisticated intruders will be tracked by mobile sensors, which will fill in the gaps in coverage, while static nodes follow a sleep schedule and will be woken when the intruder is discovered close. Our solution is compared to current techniques like Kinetic Theory Based Mobile Sensor Network (KMsn)and Mean Time to Attacks (MTTA) in terms of intrusion detection performance, energy usage, and sensor node movement distance. IDEI's parameter sensitivity is also examined via comprehensive simulations. It is clear from the theoretical analysis and simulation findings that our idea is more efficient and available.

Applications of Nanosatellites in Constellation: Overview and Feasibility Study for a Space Mission Based on Internet of Space Things Applications Used for AIS and Fire Detection.

In some geographically challenging areas (such as deserts, seas, and forests) where direct connectivity to a terrestrial network is difficult, space communication is the only option. In these remote locations, Internet of Space Things (IoST) applications can also be used successfully. In this paper, the proposed payload for IoST applications demonstrates how an Automatic Identification System (AIS) and a fire detection system can be used effectively. A space mission based on efficient and low-cost communication can use a constellation of nanosatellites to better meet this need. These two applications, which use a constellation of nanosatellites, can provide relevant university-level data in several countries as an effective policy for the transfer of space technology in an educational initiative project. To enhance educational participation and interest in space technology, this paper shares the lessons learned from the project feasibility study based on an in-depth design of a nanosatellite with several analyses (data budget, link budget, power budget, and lifetime estimation). Lastly, this paper highlights by experiments the development and application of a cost-effective sensor node for fire detection and the use of GPS to enable AIS capabilities in the IoST framework.

High accuracy sensor nodes for a peat swamp forest fire detection using ESP32 camera

<span>The </span><span lang="MS">use of smoke sensors in high-precision and low-cost forest fire detection kits needs to be developed immediately to assist the authorities in monitoring forest fires especially in remote areas more efficiently and systematically. The implementation of automatic reclosing operation allows the fire detector kit to distinguish between real smoke and non-real smoke successfully. This has profitably reduced kit errors when detecting fires and in turn prevent the users from receiving incorrect messages. However, using a smoke sensor with automatic reclosing operation has not been able to optimize the accuracy of identifying the actual smoke due to the working sensor node situation is difficult to predict and sometimes unexpected such as the source of smoke received. Thus, to further improve the accuracy when detecting the presence of smoke, the system is equipped with two digital cameras that can capture and send pictures of fire smoke to the users. The system gives the users choice of three interesting options if they want the camera to capture and send pictures to them, namely request, smoke trigger and movement for security purposes. In all cases, users can request the system to send pictures at any time. The system equipped with this camera shows the accuracy of smoke detection by confirming the actual smoke that has been detected through images sent in the user’s Telegram channel and on the Graphical User Interface (GUI) display. As a comparison of the system before and after using this camera, it was found that the system that uses the camera gives advantage to the users in monitoring fire smoke more effectively and accurately.</span>

Evaluating a Novel Gas Sensor for Ambient Monitoring in Automated Life Science Laboratories.

Air pollution and leakages of hazardous and toxic gases and chemicals are among the dangers that frequently occur at automated chemical and life science laboratories. This type of accident needs to be processed as soon as possible to avoid the harmful side effects that can happen when a human is exposed. Nitrogen oxides and volatile organic compounds are among the most prominent indoor air pollutants, which greatly affect the lifestyles in these places. In this study, a commercial MOX gas sensor, SGP41, was embedded in an IoT environmental sensor node for hazardous gas detection and alarm. The sensor can detect several parameters, including nitrogen oxide index (NOx-Index) and volatile organic compound index (VOC-Index). Several tests were conducted to detect the leakage of nitrogen oxides and volatile organic compounds in different concentrations and volumes, as well as from different leakage distances, to measure the effect of these factors on the response speed and recovery time of the sensors used. These factors were also compared between the different sensors built into the sensor node to give a comprehensive picture of the system used. The system testing results revealed that the SGP41 sensor is capable of implementing the design purposes for the target parameters, can detect a small NO2 gas leakage starting from 0.3% volume, and can detect all the tested VOC solvents ≥ 100 µL.

Embedded Monitoring Method of Greenhouse Environment based on Wireless Sensor Network

Aiming at the problem of low accuracy of greenhouse environmental monitoring, an embedded monitoring method of greenhouse environment based on wireless sensor network is studied. The embedded microprocessor S3C2410 is selected as the control chip of greenhouse environmental monitoring. The wireless sensor network is composed of wireless detection node, sink node and remote-control terminal. The temperature and humidity sensor, CO2 concentration sensor and light intensity sensor are set as the detection nodes of the wireless sensor network. Each detection sensor node is configured with wireless communication module to form a wireless sensor network to realize data communication of environmental monitoring. The distribution map method is selected to eliminate the missing data of greenhouse environmental monitoring data collected by wireless sensor network, and the weighted average method is used to fuse the monitoring data after eliminating the missing data to obtain the final greenhouse environmental monitoring results. The experimental results show that this method can effectively detect the environmental data such as temperature, humidity and light intensity of greenhouse, and the relative error of each data is less than 1%.

Ultra-Low Power Sensor Node for On-Board Railway Wagon Monitoring

Continuous real-time monitoring of unpowered railway vehicles such as general freight and heavy haul wagons is still limited by hardware scalability and power consumption challenges. This paper proposes an innovative sensor node hardware architecture that reduces power consumption and hardware costs by introducing an Analogue Fault Detector based on analogue signal processing. This technique allows data intensive fault detection and condition monitoring algorithms to be run by simple microcontrollers, reducing memory, execution time and computational requirements. An on-board wheel flat detection sensor node was tested in laboratory conditions using a hardware-in-the-loop setup, to quantify the improvements and explore the viability of the proposed sensor node architecture approach. The power required to detect a wheel flat defect in a simulated acceleration signal was reduced by one order of magnitude and the memory requirement was reduced by three orders of magnitude for the data acquisition and processing stage, compared to traditional sensor node hardware architectures. This is particularly relevant in data intensive applications using accelerometers for monitoring railway vehicles. The improvements delivered by the introduction of an Analogue Fault Detector in a sensor node hardware architecture are promising for further development of on-board ultra-low power condition monitoring sensor nodes for railway applications.

Development and power consumption analysis of low cost wireless sensor node for fire detection

Development and power consumption analysis of low cost wireless sensor node for fire detection

Development and power consumption analysis of low cost wireless sensor node for fire detection

Fire becomes a problem when it goes untamed and destroys in part or whole the ecological balance of the area. Thus arises a need to develop a system for early detection of fire with significant accuracy. In this work, a wireless sensor network has been developed for fire detection and its essential parameters, such as effective detection distance and power consumption have been monitored. The hardware developed for this system comprises of the components as a controller board and a transceiver. Without the inclusion of energy saving algorithm the system has shown a considerable lifetime and effective detection distance.

The concept of an improved acoustic wireless sensor node for leak detection and location in a water distribution networks

The concept of an improved acoustic wireless sensor node for leak detection and location in a water distribution networks

Self-powered wireless sensor node for flow and temperature sensing

This paper presents the implementation and test of a self-powered wireless sensor node using enhanced triboelectric nanogenerator (E-TriG) as both energy harvester and wireless sensor node for flow rate and temperature detection. RF microcontroller with low power consumption is included for data conversion, signal processing and wireless signal transmission. The flow-rate detection is based on the maximum voltage of a capacitor, which is charged by E-TriGs during certain period. Experiment results show that this flow sensor is capable of detecting flow rate from 5.8 m/s to 17.3 m/s with a standard deviation of 0.3% and the temperature of 24.2 °C (±0.3 °C) in the actual test. Each operation requires less than 40 ms for data sampling, processing and transmission. With a Raspberry Pi, the wireless signal can be received and delivered to Internet and therefore, can be monitored easily from any portable terminal with internet-access.

Development of a “stick-and-detect” wireless sensor node for fatigue crack detection

A fatigue crack and its precursor often serves as a source of nonlinear mechanism for ultrasonic waves, and nonlinear ultrasonic techniques have been widely studied to detect fatigue crack at its very early stage. In this study, a wireless sensor node based on nonlinear ultrasonics is developed specifically for fatigue crack detection: (1) through packaged piezoelectric transducers, ultrasonic waves at two distinctive frequencies are generated, and their modulation due to a microcrack (less than 0.1 mm in width) is detected; (2) an autonomous reference-free crack detection algorithm is developed and embedded into the sensor node, so that users can simply “stick” the sensor to a target structure and automatically “detect” a fatigue crack without relying on any history data of the target structure; and (3) the whole design of the sensor node is fulfilled in a low-power working strategy. The performance of the sensor node is experimentally validated using aluminum plates with real fatigue cracks and compared with that of a conventional wired system. Furthermore, a field test in Yeongjong Grand Bridge in South Korea has been conducted with the developed sensor nodes.

Environmental notification support using passage detecting sensor nodes

Interconnected sensor nodes can be used for a long term monitoring of widely spread ecosystems. Individual nodes can be unavailable during the runtime due to a lack of energy, disruption of communication channels, or physical damages of nodes. In this study, a new approach to transfer messages from nodes to gateways (and optional to flood gate nodes) in such dynamically disturbed networks is presented. The focus is the routing in branched line-structures, for example, flood barriers. The usage of gradient structures in each node allow tree routing, tree propagation, energy-efficient exploring broadcast, exploitation of line-structures, and collection of position information. In addition, a generic preference evaluation and decision making concept allows energy or signal quality evaluation, routing decision, structure setup decision, position estimation, synchronisation adaption, and randomisation of security approaches. It can be extended by further rules.

Performance Analysis of Wireless Sensor Networks with Non-coherent Cooperative Relay Nodes

In this paper, a non-coherent cooperative relay node selection scheme for the wireless sensor networks has been proposed. The motivation for adopting non-coherent combining scheme is due to low complexity in a sensor node for signal detection. Its performance was evaluated in terms of the transfer capacity, the energy consumption of the interested node, and its validity of a cooperative node selection. The cooperative relay node selection was made in order to improve the intermediate wireless link between the source and the destination nodes. The energy factor was considered as a performance index of the proposed scheme. The energy factor for the interested sensor node was obtained by combining the signal of the direct path and that of the relay path. The numerical results showed that the proposed scheme can improve the transfer capacity and the energy reduction of the interested node. Moreover, it can prevent the ineffective combining of the cooperative relay node which can cause the loss of the transfer capacity and the energy consumption.

Wireless Sensor Node for Gas Pipeline Leak Detection and Location

Many different wireless sensor nodes for gas pipeline leak detection and location has been proposed but still there are challenges particularly on environmental issues and signal accuracy. This paper discusses theories and environmental constraints for wireless sensor nodes, a case study of Dar es Salaam Tanzania and finally presents a design and simulation results of the proposed wireless sensor node using Proteus Design Suite for detecting frequency of sound exited by jetting gas, leaking from higher pressurised gas pipeline. This kind of proposed system can be useful to gas companies or industries whereby gas transportation is done. General Terms Sensor node, Gas leak detection, Pipeline monitoring, Acoustic sensor, Speed of sound in air

Probabilistic Model for Single and Multi-Sensing Intrusion Detection in Wireless Sensor Networks

Wireless Sensor Networks consists of tiny devices capable of processing, routing the sensed data and are capable of detecting the intruders. The process of detecting any suspected(anomalous) moving object(attacker) within the reach of a Wireless Sensor Network area is referred to as intrusion detection. In this paper, we propose an algorithm to detect the intruder by the cluster heads in a 2D and 3D homogeneous Wireless Sensor Networks. This algorithm overcomes the attacks on implementation and also, reduces the energy consumption. The proposed algorithm considers Single Sensing and Multi-Sensing Intrusion Detection using minimum number of sensor nodes and a probabilistic model has been developed for both 2D and 3D homogeneous networks. Simulation results show that the power analysis attack and energy consumption is minimized by activating only few sensor nodes for detection and using only few sensor nodes for processing of data. The performance of the proposed algorithm is better compared to using all the sensor nodes for detection where the energy consumption is more.

Enabling Wireless Sensor Nodes for Self-Contained Jamming Detection

Jamming is an easy to execute attack to which wireless sensor networks are extremely vulnerable. If the application requires reliability, jamming needs to be detected and reported in order to cope with this attack. In this article, we investigate different approaches to identify jamming. Available jamming detection schemes primarily suffer from the usage of fixed thresholds as well as required effort. We adapted a variance-based estimate of signal-tonoise ratio measurements, called significance analysis, to the minor resources and computing efforts of wireless sensor nodes. As a start, we used real measurement data for theoretical analysis of the methods under investigation. Independently of the location of the jamming device, our significance analysis approach provides an immediate indication of jamming and can in theory be run with almost least effort, i.e., with O(14). On top of that, we implemented this approach on our state of the art sensor node and tested it in a real world outdoor setting. Our jamming detection engine monitors the wireless channel with a sampling rate of 10 ms. It returns a jamming detection decision within less than 5 ms while though achieving a detection accuracy in between 84 to 99 percent.

Robust Multi-Bernoulli Sensor Selection for Multi-Target Tracking in Sensor Networks

This letter addresses the sensor selection problem for tracking multiple dynamic targets within a sensor network. Since the bandwidth and energy of the sensor network are constrained, it would not be feasible to directly use the entire information of sensor nodes for detection and tracking of the targets and hence the need for sensor selection. Our sensor selection solution is formulated using the multi-Bernoulli random finite set framework. The proposed method selects a minimum subset of sensors which are most likely to provide reliable measurements. The overall scheme is a robust method that works in challenging scenarios where no prior information are available on clutter intensity or sensor detection profile. Simulation results demonstrate successful sensor selection in a challenging case where five targets move in a close vicinity to each other. Comparative results show the superior performance of our method in terms of accuracy of estimating the number of targets and their states.

Radio Frequency Based Emergency Exit Node Technology

This paper introduces an indoor sensor fusion wireless communication device which provides the Location Based Service (LBS) using fire prevention facility. The proposed system can provide information in real time by optimizing the hardware of Wi-Fi technology. The proposed system can be applied to a fire prevention facility (i.e., emergency exit) and provide information such as escape way, emergency exit location, and accident alarm to smart phone users, dedicated terminal holders, or other related organizations including guardians, which makes them respond instantly with lifesaving, emergency mobilization, etc. Also, the proposed system can be used as a composite fire detection sensor node with additional fire and motion detect sensors.

Wireless Magnetic Sensor Node for Vehicle Detection With Optical Wake-Up

Vehicle detectors provide essential information about parking occupancy and traffic flow. To cover large areas that lack a suitable electrical infrastructure, wired sensors networks are impractical because of their high deployment and maintenance costs. Wireless sensor networks (WSNs) with autonomous sensor nodes can be more economical. Vehicle detectors intended for a WSN should be small, sturdy, low power, cost-effective, and easy to install and maintain. Currently available vehicle detectors based on inductive loops, ultrasound, infrared, or magnetic sensors do not fulfill the requirements above, which has led to the search for alternative solutions. This paper presents a vehicle detector which includes a magnetic and an optical sensor and is intended as sensor node for use with a WSN. Magnetic sensors based on magnetoresistors are very sensitive and can detect the magnetic anomaly in the Earth's magnetic field that results from the presence of a car, but their continuous operation would drain more than 1.5 mA at 3 V, hence limiting the autonomy of a battery-supplied sensor node. Passive, low-power optical sensors can detect the shadow cast by car that covers them, but are prone to false detections. The use of optical triggering to wake-up a magnetic sensor, combined with power-efficient event-based software, yields a simple, compact, reliable, low-power sensor node for vehicle detection whose quiescent current drain is 5.5 μA. This approach of using a low-power sensor to trigger a second more specific sensor can be applied to other autonomous sensor nodes.