An Efficient IIoT-Based Smart Sensor Node for Predictive Maintenance of Induction Motors

Predictive maintenance is a vital aspect of the industrial sector,and the use of Industrial Internet of Things(IIoT)sensor nodes is becoming increasingly popular for detecting motor faults and monitoring motor conditions.An integrated approach for acquiring,processing,and wirelessly transmitting a large amount of data in predictive maintenance applications remains a significant challenge.This study presents an IIoT-based sensor node for industrial motors.The sensor node is designed to acquire vibration data on the radial and axial axes of the motor and utilizes a hybrid approach for efficient data processing via edge and cloud platforms.The initial step of signal processing is performed on the node at the edge,reducing the burden on a centralized cloud for processing data from multiple sensors.The proposed architecture utilizes the lightweight Message Queue Telemetry Transport(MQTT)communication protocol for seamless data transmission from the node to the local and main brokers.The broker’s bridging allows for data backup in case of connection loss.The proposed sensor node is rigorously tested on a motor testbed in a laboratory setup and an industrial setting in a rice industry for validation,ensuring its performance and accuracy in real-world industrial environments.The data analysis and results from both testbed and industrial motors were discussed using vibration analysis for identifying faults.The proposed sensor node is a significant step towards improving the efficiency and reliability of industrial motors through realtime monitoring and early fault detection,ultimately leading to minimized unscheduled downtime and cost savings.

High Efficient Reconfigurable and Self Testable Architecture for Sensor Node

Sensor networks are regularly sent to monitor certain physical properties that run in length from divisions of a second to many months or indeed several years.Nodes must advance their energy use for expanding network lifetime.The fault detection of the network node is very significant for guaranteeing the correctness of monitoring results.Due to different network resource constraints and malicious attacks,security assurance in wireless sensor networks has been a difficult task.The implementation of these features requires larger space due to distributed module.This research work proposes new sensor node architecture integrated with a self-testing core and cryptoprocessor to provide fault-free operation and secured data transmission.The proposed node architecture was designed using Verilog programming and implemented using the Xilinx ISE tool in the Spartan 3E environment.The proposed system supports the real-time application in the range of 33 nanoseconds.The obtained results have been compared with the existing Microcontroller-based system.The power consumption of the proposed system consumes only 3.9 mW,and it is only 24%percentage of AT mega-based node architecture.

Fault Pattern Diagnosis and Classification in Sensor Nodes Using Fall Curve

The rapid expansion of Internet of Things(IoT)devices deploys various sensors in different applications like homes,cities and offices.IoT applications depend upon the accuracy of sensor data.So,it is necessary to predict faults in the sensor and isolate their cause.A novel primitive technique named fall curve is presented in this paper which characterizes sensor faults.This technique identifies the faulty sensor and determines the correct working of the sensor.Different sources of sensor faults are explained in detail whereas various faults that occurred in sensor nodes available in IoT devices are also presented in tabular form.Fault prediction in digital and analog sensors along with methods of sensor fault prediction are described.There are several advantages and disadvantages of sensor fault prediction methods and the fall curve technique.So,some solutions are provided to overcome the limitations of the fall curve technique.In this paper,a bibliometric analysis is carried out to visually analyze 63 papers fetched from the Scopus database for the past five years.Its novelty is to predict a fault before its occurrence by looking at the fall curve.The sensing of current flow in devices is important to prevent a major loss.So,the fall curves of ACS712 current sensors configured on different devices are drawn for predicting faulty or non-faulty devices.The analysis result proved that if any of the current sensors gets faulty,then the fall curve will differ and the value will immediately drop to zero.Various evaluation metrics for fault prediction are also described in this paper.At last,this paper also addresses some possible open research issues which are important to deal with false IoT sensor data.

TelG Mote: A Green Wireless Sensor Node Platform for Smart Home and Ambient Assisted Living

The wireless sensor network （WSN） consists of sensor nodes that interact with each other to collectively monitor environmental or physical conditions at different locations for the intended users. One of its potential deployments is in the form of smart home and ambient assisted living （SHAAL）to measure patients or elderly physiological signals, control home appliances, and monitor home. This paper focuses on the development of a wireless sensor node platform for SHAAL application over WSN which complies with the IEEE 802.15.4 standard and operates in 2.4 GHz ISM （industrial, scientific, and medical） band. The initial stage of SHAAL application development is the design of the wireless sensor node named TelG mote. The main features of TelG mote contributing to the green communications include low power consumption, wearable, flexible, user-friendly, and small sizes. It is then embedded with a self-built operating system named WiseOS to support customized operation. The node can achieve a packet reception rate （PRR） above 80% for a distance of up to 8 m. The designed TelG mote is also comparable with the existing wireless sensor nodes available in the market.

Transmission performance of 2.4 GHz wireless sensor nodes when used in a working-face environment

Wireless sensor nodes have the advantage of being low-cost,easily deployed and of good mobility.If deployed in an underground mine with existing underground transmission systems a wireless sensor network can improve the collection of information.To get good transmission performance for 2.4 GHz wireless sensor nodes at the working face we calculated the reflection properties of electromagnetic waves from a flat metal plate.Using the cascade impedance method(CIM),we studied transmission attenuation and compared the results to actual tests.The results show that the effective transmission distance of 2.4 GHz wireless sensor nodes meets the stipulations of the ZigBee protocol.

Key Algorithm on Medical Inter net of Things Sensor Node Based on Magnetic Induction Tomography

This paper focuses on the key issues of information processing in the new sensing technology-electromagnetic induction tomography and depth theoretical study and experimental simulation have been conducted.In this study,Labview is used to drive the data acquisition card to control the signal generation and acquisition,and Matlab is used to achieve algorithms such as Fast Fourier Transformation (FFT) algorithm,relevant law algorithm and the classical method algorithm.The simulation results show this software system enables successful digital phase identification and the phase difference resolution of 0.10 can be achieved,which is consistent with theoretical analysis.It can also be seen that software system based on Labview and Matlab is a successful method to identify the phase difference in magnetic induction tomography system,which can meet the measurement needs of sensor nodes,laying the basis for the further development of medical IoT study.

Hardware/Compiler Memory Protection in Sensor Nodes

With reference to sensor node architectures, we consider the problem of supporting forms of memory protection through a hardware/compiler approach that takes advantage of a low-cost protection circuitry inside the microcontroller, interposed between the processor and the storage devices. Our design effort complies with the stringent limitations existing in these architectures in terms of hardware complexity, available storage and energy consumption. Rather that precluding deliberately harmful programs from producing their effects, our solution is aimed at limiting the spread of programming errors outside the memory scope of the running program. The discussion evaluates the resulting protection environment from a number of salient viewpoints that include the implementation of common protection paradigms, efficiency in the distribution and revocation of access privileges, and the lack of a privileged (kernel) mode.

Cognitive Radio Sensor Node Empowered Mobile Phone for Explosive Trace Detection

Usefulness of sensor network applications in human life is increasing day by day and the concept of wireless connection promises new application areas. Sensor network can be very beneficial in saving human life from terrorist attacks causing explosion in certain areas leading to casualties. But realization of the sensor network application in explosive detection requires high scalability of the sensor network and fast transmission of the information through real time monitoring and control. In this paper a novel mechanism for explosive trace detection in any populated area by the use of mobile telephony has been described. The aim is to create a system that will assure common men, local population and above all the nation a secured environment, without disturbing their freedom of movement. It would further help the police in detection of explosives more quickly, isolation of suicide bombers, remediation of explosives manufacturing sites, and forensic and criminal investigation. To achieve this, the paper has projected an idea that can combine the strength of the mobile phones, the polymer sensor and existing cellular network. The idea is to design and embed a tiny cog-nitive radio sensor node into the mobile phone that adapts to the changing environment by analyzing the RF surroundings and adjusting the spectrum use appropriately. The system would be capable of detecting explo-sives within a defined territory. It would communicate the location of the detected explosives to the respec-tive service provider, which in turn would inform the law and enforcement agency or Police.

Development of Battery-Less Wireless Current Sensor Node Utilizing Charging Time of Capacitors with Wide Measurement Range

We report a novel battery-less wireless current sensor node without an analog to digital converter (ADC). If a capacitor is charged using a current transformer (CT) and a rectifying circuit, the charging time depends on the current flowing through a power line. In the case that the node transmits data every time when voltage of the capacitor exceeds a threshold voltage, we can indirectly measure the current by measuring the transmission intervals. In this method, the circuit of the node can be simplified and power consumption for the wireless transmission can be decreased because the measured current data does not need to be included in the transmitted packet. However, the measurable range is about single digit because the transmission interval decreases suddenly as the current increases. In this work, we have ex- panded the range using one CT, one wireless transmission module, and two charging circuits that include different load resistors connected in series. The results indicated that the measurable range was from 0.5 A to 50 A.

Steadfast Energy Proficient Sensor Node Activation System in Wireless Networks Lifetime Enhancement

The wireless sensor network (WSN) is one of the budding exploring areas and fast rising fields in wireless communications. The sensor nodes in the network are generally small-size, low-cost, low-power and multi-function capabilities. Wireless sensor networks (WSNs) are used for various applications;since numerous sensor nodes are usually deployed on remote and inaccessible places, the employment and preservation should be easy and scalable. Sensor nodes in the field being run out of energy quickly has been an issue and many energy efficient routing protocols have been proposed to solve this problem and preserve the long life of the network. This paper work proposes a hierarchical based node activation routing technique which shows energy efficiency. This technique selects cluster head with highest residual energy in each communication round of transmission to the base station from the cluster heads. Hierarchical based node activation routing technique with different levels of hierarchy simulation results prolongs the lifetime of the network compared to other clustering schemes and communication rounds of simulation increase significantly.

A low power 8-bit successive approximation register A/D for a wireless body sensor node

A power efficient 8-bit successive approximation register（SAR） A/D for the vital sign monitoring of a wireless body sensor network（WBSN） is presented.A charge redistribution architecture is employed.The prototype A/D is fabricated in 0.18μm CMOS.The A/D achieves 7.5ENOB with sampling rate varying from 64 kHz to 1.5 MHz. The power consumption varies from 10.8 to 225.7μW.

Grid-Based Localization Mechanism with Mobile Reference Node in Wireless Sensor Networks

Wireless sensor networks （WSNs） are based on monitoring or managing the sensing area by using the location information with sensor nodes. Most sensor nodes require hardware support or receive packets with location information to estimate their locations, which needs lots of time or costs. In this paper we proposed a localization mechanism using a mobile reference node （MRN） and trilateration in WSNs to reduce the energy consumption and location error. The simulation results demonstrate that the proposed mechanism can obtain more unknown nodes locations by the mobile reference node moving scheme and will decreases the energy consumption and average ocation error.

无线传感器网络基于测距的节点定位算法综述OverviewoftheNodeLocalizationAlgorithmBasedonRangingofWirelessSensorNetworks

基于测距的定位方法对测量的距离信息运用几何知识求解未知节点的位置,常用在定位精度较高的领域,可在误差、能耗、受环境因素影响等方面进行优化。本文对基于测距的无线传感器网络节点定位算法进行详细地分析和比较。

Genetic-Chicken Swarm Algorithm for Minimizing Energy in Wireless Sensor Network

Wireless Sensor Network(WSN)technology is the real-time applica-tion that is growing rapidly as the result of smart environments.Battery power is one of the most significant resources in WSN.For enhancing a power factor,the clustering techniques are used.During the forward of data in WSN,more power is consumed.In the existing system,it works with Load Balanced Cluster-ing Method(LBCM)and provides the lifespan of the network with scalability and reliability.In the existing system,it does not deal with end-to-end delay and deliv-ery of packets.For overcoming these issues in WSN,the proposed Genetic Algo-rithm based on Chicken Swarm Optimization(GA-CSO)with Load Balanced Clustering Method(LBCM)is used.Genetic Algorithm generates chromosomes in an arbitrary method then the chromosomes values are calculated using Fitness Function.Chicken Swarm Optimization(CSO)helps to solve the complex opti-mization problems.Also,it consists of chickens,hens,and rooster.It divides the chicken into clusters.Load Balanced Clustering Method(LBCM)maintains the energy during communication among the sensor nodes and also it balances the load in the gateways.The proposed GA-CSO with LBCM improves the life-span of the network.Moreover,it minimizes the energy consumption and also bal-ances the load over the network.The proposed method outperforms by using the following metrics such as energy efficiency,ratio of packet delivery,throughput of the network,lifetime of the sensor nodes.Therefore,the evaluation result shows the energy efficiency that has achieved 83.56%and the delivery ratio of the packet has reached 99.12%.Also,it has attained linear standard deviation and reduced the end-to-end delay as 97.32 ms.

Node deployment strategy optimization for wireless sensor network with mobile base station

The optimization of network performance in a movement-assisted data gathering scheme was studied by analyzing the energy consumption of wireless sensor network with node uniform distribution. A theoretically analytical method for avoiding energy hole was proposed. It is proved that if the densities of sensor nodes working at the same time are alternate between dormancy and work with non-uniform node distribution. The efficiency of network can increase by several times and the residual energy of network is nearly zero when the network lifetime ends.

Design and performance analysis of wireless sensor network location node system for underground mine

Aiming at the application of a wireless sensor network to locating miners in underground mine,we design a wireless sensor network location node system,considering the communication performance and the intrinsic safety. The location node system consists of a mobile node,several fixed nodes,and a sink node,all of whose circuits were designed based on CC2430. A varistor and a RC circuit were used in the reset circuit of a sensor node to guarantee the intrinsic safety by reducing discharge energy,the theoretical analysis of the discharge energy shows that the reset circuit is an intrinsic safety one. The analysis and simulation about the performance of the location node system are discussed,such as network communication delay and packet loss rate,the results show that the highest network communication delay of the system is about 0.11 seconds,and the highest packet loss rate is about 0.13,which assures the location node system has a high reliability,and can locate miners in the underground mine.

Neighbor-Based Malicious Node Detection in Wireless Sensor Networks

The primary function of wireless sensor networks is to gather sensor data from the monitored area. Due to faults or malicious nodes, however, the sensor data collected or reported might be wrong. Hence it is important to detect events in the presence of wrong sensor readings and misleading reports. In this paper, we present a neighbor-based malicious node detection scheme for wireless sensor networks. Malicious nodes are modeled as faulty nodes behaving intelligently to lead to an incorrect decision or energy depletion without being easily detected. Each sensor node makes a decision on the fault status of itself and its neighboring nodes based on the sensor readings. Most erroneous readings due to transient faults are corrected by filtering, while nodes with permanent faults are removed using confidence-level evaluation, to improve malicious node detection rate and event detection accuracy. Each node maintains confidence levels of itself and its neighbors, indicating the track records in reporting past events correctly. Computer simulation shows that most of the malicious nodes reporting against their own readings are correctly detected unless they behave similar to the normal nodes. As a result, high event detection accuracy is also maintained while achieving low false alarm rate.

A Malicious and Malfunctioning Node Detection Scheme for Wireless Sensor Networks

Wireless sensor networks are often used to monitor physical and environmental conditions in various regions where human access is limited. Due to limited resources and deployment in hostile environment, they are vulnerable to faults and malicious attacks. The sensor nodes affected or compromised can send erroneous data or misleading reports to base station. Hence identifying malicious and faulty nodes in an accurate and timely manner is important to provide reliable functioning of the networks. In this paper, we present a malicious and malfunctioning node detection scheme using dual-weighted trust evaluation in a hierarchical sensor network. Malicious nodes are effectively detected in the presence of natural faults and noise without sacrificing fault-free nodes. Simulation results show that the proposed scheme outperforms some existing schemes in terms of mis-detection rate and event detection accuracy, while maintaining comparable performance in malicious node detection rate and false alarm rate.