An Insight Survey on Sensor Errors and Fault Detection Techniques in Smart Spaces

The widespread adoption of the Internet of Things (IoT) has transformed various sectors globally, making themmore intelligent and connected. However, this advancement comes with challenges related to the effectiveness ofIoT devices. These devices, present in offices, homes, industries, and more, need constant monitoring to ensuretheir proper functionality. The success of smart systems relies on their seamless operation and ability to handlefaults. Sensors, crucial components of these systems, gather data and contribute to their functionality. Therefore,sensor faults can compromise the system’s reliability and undermine the trustworthiness of smart environments.To address these concerns, various techniques and algorithms can be employed to enhance the performance ofIoT devices through effective fault detection. This paper conducted a thorough review of the existing literature andconducted a detailed analysis.This analysis effectively links sensor errors with a prominent fault detection techniquecapable of addressing them. This study is innovative because it paves theway for future researchers to explore errorsthat have not yet been tackled by existing fault detection methods. Significant, the paper, also highlights essentialfactors for selecting and adopting fault detection techniques, as well as the characteristics of datasets and theircorresponding recommended techniques. Additionally, the paper presents amethodical overview of fault detectiontechniques employed in smart devices, including themetrics used for evaluation. Furthermore, the paper examinesthe body of academic work related to sensor faults and fault detection techniques within the domain. This reflectsthe growing inclination and scholarly attention of researchers and academicians toward strategies for fault detectionwithin the realm of the Internet of Things.

Study on Temperature Modulation Techniques for Micro Gas Sensors

The sensitivity and selectivity of gas sensors are related with not only sensing material,but also their operating temperatures.Applying this property,temperature modulation technique has been proposed to improve the selectivity of gas sensors.With a newly developed alumina based micro gas sensor,the sensitivity to CO and CH_4 at different operating temperatures was investigated.By modulating the temperature of the sensor at pulse and sine wave modes with different frequencies and amplitudes,the dynamic responses of the sensor were measured and processed.Results show that the modulating waveshape plays an important role in the improvement of selectivity,while the influence of frequency is small at the suitable sampling frequency in the range of 25 mHz～200 mHz.

A novel slot scheduling technique for duty-cycle based data transmission for wireless sensor network

The duty cycling process involves turning a radio into an active and dormant state for conserving energy. It is a promising approach for designing routing protocols for a resource-constrained Wireless Sensor Networks (WSNs). In the duty cycle-based WSNs, the network lifetime is improved and the network transmission is increased as compared to conventional routing protocols. In this study, the active period of the duty cycle is divided into slots that can minimize the idle listening problem. The slot scheduling technique helps determine the most efficient node that uses the active period. The proposed routing protocol uses the opportunistic concept to minimize the sender waiting problem. Therefore, the forwarder set will be selected according to the node's residual active time and energy. Further, the optimum routing path is selected to achieve the minimum forwarding delay from the source to the destination. Simulation analysis reveals that the proposed routing scheme outperforms existing schemes in terms of the average transmission delay, energy consumption, and network throughput.

Research on Nanometer Technique and Low-Work-Loss Sensor

The preparation process of the CO gas sensor used at normal temperature is presented.The electric conductance of this type of sensor evolved oscillation from regularly when the sensor is exposed to low level CO gas.The gas sensing mechanism was investigated by its crystalline structure.The mechanism of information sensing,which was the concurrence of the grain boundary barrier control and the crystal surface control,is discussed.

An Efficient Priority Based Routing Technique That Maximizes the Lifetime and Coverage of Wireless Sensor Networks

Recent development in sensor technologies makes wireless sensor networks (WSN) very popular in the last few years. A limitation of most popular sensors is that sensor nodes have a limited battery capacity that leads to lower the lifetime of WSN. For that, it raises the need to develop energy efficient solutions to keep WSN functioning for the longest period of time. Due to the fact that most of the nodes energy is spent on data transmission, many routing techniques in the literature have been proposed to expand the network lifetime such as the Online Maximum Lifetime heuristics (OML) and capacity maximization (CMAX). In this paper, we introduce an efficient priority based routing power management heuristic in order to increase both coverage and extend lifetime by managing the power at the sensor level. We accomplished that by setting priority metric in addition to dividing the node energy into two ratios;one for the sensor node originated data and the other part is for data relays from other sensors. This heuristic, which is called pERPMT (priority Efficient Routing Power Management Technique), has been applied to two well know routing techniques. Results from running extensive simulation runs revealed the superiority of the new methodology pERPMT over existing heuristics. The pEPRMT increases the lifetime up to 77% and 54% when compared to OML and CMAX respectively.

Hybrid Sensor Selection Technique for Lifetime Extension of Wireless Sensor Networks

Energy conservation is a crucial issue to extend the lifetime of wireless sensor networks(WSNs)where the battery capacity and energy sources are very restricted.Intelligent energy-saving techniques can help designers overcome this issue by reducing the number of selected sensors that report environmental measurements by eliminating all replicated and unrelated features.This paper suggests a Hybrid Sensor Selection(HSS)technique that combines filter-wrappermethod to acquire a rich-informational subset of sensors in a reasonable time.HSS aims to increase the lifetime of WSNs by using the optimal number of sensors.At the same time,HSS maintains the desired level of accuracy and manages sensor failures with the most suitable number of sensors without compromising the accuracy.The evaluation of the HSS technique has adopted four experiments by using four different datasets.These experiments show that HSS can extend the WSNs lifetime and increase the accuracy using a sufficient number of sensors without affecting theWSNfunctionality.Furthermore,to ensure HSS credibility and reliability,the proposed HSS technique has been compared to other corresponding methodologies and shows its superiority in energy conservation at premium accuracy measures.

3-D Grid-Based Localization Technique in Mobile Sensor Networks

Considering the environmental protection, forest fire becomes a more and more serious problem and requires more concerns. This paper provides an efficient method for fire monitoring and detection in forests using wireless sensor network technology. The proposed technique estimates the location of a sensor node based on the current set of hop-count values, which are collected through the anchor nodes’ broadcast. Our algorithm incorporates two salient features;grid-based output and event-triggering mechanism, to improve the accuracy while reducing the power consumption. Through the computer simulation, the output region obtained from our algorithm can always cover the target node. In addition, the algorithm was implemented and tested with a set of Crossbow sensors. Experimental results demonstrated the high feasibility and worked well in real environment.

Energy Proficient Reliable Rim Routing Technique for Wireless Heterogeneous Sensor Networks Lifespan Fortification

Sensor nodes are mainly shielded in the field with limited power supply. In Wireless Sensor Networks, there must be a requirement of an efficient power management, because sensor nodes are deployed in unman attended area with non-rechargeable batteries. Power management can be done by different methods of routing protocols. The proposed Reliable Rim Routing (3R) technique is based on hybrid routing protocol for homogeneous and heterogeneous system for WSNs to ameliorate the performance of the overall system. In 3R, total node deployment area can be multipart in terms of rim and in each rim, and some of the sensor nodes transmit their sensed data directly to base station, and meanwhile remaining sensor nodes send the data through clustering technique to base station like SEP. Proposed 3R technique implementation proves its enhanced WSNs lifetime of 70% energy consumption and 40% throughput compared with existing protocols. Simulation and evaluation results outperformed in terms of energy consumption with increased throughput and network lifetime.

Structural Surface Crack Monitoring Method Based on Electrical Potential Technique and Modern Surface Technology

Crack monitoring plays a great role in modern structural health monitoring, however, most of the conventional crack inspections have disadvantages in terms of the accuracy, expense, reliability, durability and level of instrumentation required. Thus, development of a simple and reliable crack inspection technique that allows continuous monitoring has been desired. In this paper, electrical potential technique and modern surface technology are employed together to develop a new structural surface crack monitoring method. A special crack monitoring coating sensor based on electrical potential technique was deposited on the hot spot of the structure by modern surface technology. The sensor consists of three layers： the isolated layer, the sensing layer and the protective layer. The isolated layer is prepared by anodic oxidation technology, the sensing layer is made of ion plated copper, and the protective layer is made of silicone. The thickness of each layer is at micrometer magnitude. The electrical conductivity of the sensor is very stable, and the fatigue performance of the specimen with or without coating sensor is nearly unchanged. The crack monitoring experiment result shows that there are two sudden rises of the coating sensor electrical potential values, corresponding to different stages of the crack initiation and propagation. Since the width of the surface coating sensor is only 0.5 mm, this crack monitoring sensor can detect the propagation of cracks less than 0.5 mm long. The method proposed takes the simplicity of electrical potential technique and can monitor surface crack of nearly all kinds of structures precisely. The results of this paper may form the basis of a new crack monitoring system.

Morphological Engineering of Sensing Materials for Flexible Pressure Sensors and Artificial Intelligence Applications

As an indispensable branch of wearable electronics,flexible pressure sensors are gaining tremendous attention due to their extensive applications in health monitoring,human-machine interaction,artificial intelligence,the internet of things,and other fields.In recent years,highly flexible and wearable pressure sensors have been developed using various materials/structures and transduction mechanisms.Morphological engineering of sensing materials at the nanometer and micrometer scales is crucial to obtaining superior sensor performance.This review focuses on the rapid development of morphological engineering technologies for flexible pressure sensors.We discuss different architectures and morphological designs of sensing materials to achieve high performance,including high sensitivity,broad working range,stable sensing,low hysteresis,high transparency,and directional or selective sensing.Additionally,the general fabrication techniques are summarized,including self-assembly,patterning,and auxiliary synthesis methods.Furthermore,we present the emerging applications of high-performing microengineered pressure sensors in healthcare,smart homes,digital sports,security monitoring,and machine learning-enabled computational sensing platform.Finally,the potential challenges and prospects for the future developments of pressure sensors are discussed comprehensively.

Direction finding of coexisted independent and coherent signals using electromagnetic vector sensor

The existing direction of arrival （DOA） estimation algorithms based on the electromagnetic vector sensors array barely deal with the coexisting of independent and coherent signals. A two-dimensional direction finding method using an L-shape electromagnetic vector sensors array is proposed. According to this method, the DOAs of the independent signals and the coherent signals are estimated separately, so that the array aperture can be exploited sufficiently. Firstly, the DOAs of the independent signals are estimated by the estimation of signal parameters via rotational invariance techniques, and the influence of the co- herent signals can be eliminated by utilizing the property of the coherent signals. Then the data covariance matrix containing the information of the coherent signals only is obtained by exploiting the Toeplitz property of the independent signals, and an improved polarimetric angular smoothing technique is proposed to de-correlate the coherent signals. This new method is more practical in actual signal environment than common DOA estimation algorithms and can expand the array aperture. Simulation results are presented to show the estimating performance of the proposed method.

Fiber optic strain twin-sensor-array for smart structural health monitoring

A multiplexed white light interferometric fiber optic twin-sensor-array was designed to monitor the structural health of large buildings.In this sensing system,based on a Michelson interferometer,an optical path matching technique is used to demodulate each twin-sensor.Each twin-sensor-array consists of a 2×N sensing element linked by a 3 dB coupler.When one of the twin-sensor is used to measure strain,variations caused by temperature can be compensated for by referencing the other twin-sensor.The multiplexing capacity of the sensing scheme has been analyzed and experimental results with a 2×3 twin-sensor-array are given.

On-Machine Measurement of the Straightness and Tilt Errors of a Linear Slideway Using a New Four-Sensor Method

Although there are some multi-sensor methods for measuring the straightness and tilt errors of a linear slideway, they need to be further improved in some aspects, such as suppressing measurement noise and reducing precondition.In this paper, a new four-sensor method with an improved measurement system is proposed to on-machine separate the straightness and tilt errors of a linear slideway from the sensor outputs, considering the influences of the reference surface profile and the zero-adjustment values. The improved system is achieved by adjusting a single sensor to di erent positions. Based on the system, a system of linear equations is built by fusing the sensor outputs to cancel out the e ects of the straightness and tilt errors. Three constraints are then derived and supplemented into the linear system to make the coe cient matrix full rank. To restrain the sensitivity of the solution of the linear system to the measurement noise in the sensor outputs, the Tikhonov regularization method is utilized. After the surface profile is obtained from the solution, the straightness and tilt errors are identified from the sensor outputs. To analyze the e ects of the measurement noise and the positioning errors of the sensor and the linear slideway, a series of computer simulations are carried out. An experiment is conducted for validation, showing good consistency. The new four-sensor method with the improved measurement system provides a new way to measure the straightness and tilt errors of a linear slideway, which can guarantee favorable propagations of the residuals induced by the noise and the positioning errors.

Network Quality Assessment in Heterogeneous Wireless Settings: An Optimization Approach

The identification of an effective network which can efficiently meet the service requirements of the target,while maintaining ultimate performance at an increased level is significant and challenging in a fully interconnected wireless medium.The wrong selection can contribute to unwanted situations like frustrated users,slow service,traffic congestion issues,missed and/or interrupted calls,and wastefulness of precious network components.Conventional schemes estimate the handoff need and cause the network screening process by a single metric.The strategies are not effective enough because traffic characteristics,user expectations,network terminology and other essential device metrics are not taken into account.This article describes an intelligent computing technique based on Multiple-Criteria Decision-Making(MCDM)approach developed based on integrated Fuzzy AHP-TOPSIS which ensures flexible usability and maximizes the experience of end-users in miscellaneous wireless settings.In different components the handover need is assessed and the desired network is chosen.Further,fuzzy sets provide effective solutions to address decision making problems where experts counter uncertainty to make a decision.The proposed research endeavor will support designers and developers to identify,select and prioritize best attributes for ensuring flexible usability in miscellaneous wireless settings.The results of this research endeavor depict that this proposed computational procedure would be the most conversant mechanism for determining the usability and experience of end-users.

Modeling, Simulation and Experimental Studies of Refractometric Fiber Optic Sensor

Refractometric fiber optic sensors have a number of applications in industry due to advantages like remote sensing ability, compact size, easy to fit, etc. A refractometric sensor contains a pair of parallel fibers and a gap between the sensor probe and reflector, wherein the liquid whose refractive index is to be measured is filled. This paper describes the importance of mathematical modeling of this sensor. Ray tracing approach is used to model the sensor mathematically. This mathematical model is generalized for any scenario which is useful to avoid tedious trial and error techniques to design the sensor prototype. Mathematical modelling is a useful tool to optimize the gap distance for a detection of refractive index of liquid. The model is developed and analyzed rigorously considering adulteration of diesel by kerosene where refractive index varies from 1.44 to 1.46. Simulation experiments are carried out to optimize the gap distance which is found to be 6.8 mm using both models. Experiments are carried out where sensor probe is fabricated and results are analyzed. It is observed that for suggested gap distance sensor output varies almost linear over the entire range.

A Novel Low-Complexity Low-Latency Power Efficient Collision Detection Algorithm for Wireless Sensor Networks

Collision detection mechanisms in Wireless Sensor Networks (WSNs) have largely been revolving around direct demodulation and decoding of received packets and deciding on a collision based on some form of a frame error detection mechanism, such as a CRC check. The obvious drawback of full detection of a received packet is the need to expend a significant amount of energy and processing complexity in order to fully decode a packet, only to discover the packet is illegible due to a collision. In this paper, we propose a suite of novel, yet simple and power-efficient algorithms to detect a collision without the need for full-decoding of the received packet. Our novel algorithms aim at detecting collision through fast examination of the signal statistics of a short snippet of the received packet via a relatively small number of computations over a small number of received IQ samples. Hence, the proposed algorithms operate directly at the output of the receiver's analog-to-digital converter and eliminate the need to pass the signal through the entire. In addition, we present a complexity and power-saving comparison between our novel algorithms and conventional full-decoding (for select coding schemes) to demonstrate the significant power and complexity saving advantage of our algorithms.

Robust Cubic-Based 3-D Localization for Wireless Sensor Networks

The rapid progress of wireless communication and the availability of many small-sized, light-weighted and low-cost communication and computing devices nowadays have greatly impacted the development of wireless sensor network. Localization using sensor network has attracted much attention for its comparable low-cost and potential use with mon- itoring and targeting purposes in real and hostile application scenarios. Currently, there are many available approaches to locating persons/things based on global positioning system (GPS) and radio-frequency identification (RFID) technologies. However, in some application scenario, e.g., disaster rescue application, such localization devices may be damaged and may not provide the location information of the survivors. The main goal of this paper is to design and develop a robust localization technique for human existence detection in case of disasters such as earthquake or fire. In this paper, we propose a 3-D localization technique based on the hop-count data collected from sensor anchors to estimate the location of the activated sensor mote in 3-D coordination. Our algorithm incorporates two salient features, cubic-based output and event-triggering mechanism, to guarantee both improved accuracy and power efficiency. Both simulation and experimental results indicate that the proposed algorithm can improve the localization precision of the human existence and work well in real environment.

基于4H-SiC APD单光子探测的主动淬灭电路研究

为了对比不同类型淬灭电路对4H-SiC雪崩光电二极管(APD)探测性能的影响,采用被动淬灭电路(PQC)和主动淬灭电路(AQC),对两种类型SiC紫外APD进行了单光子探测实验,发现在PQC较长死区时间内,会频发后脉冲现象,导致APD的暗计数率(DCR)较高,从而降低器件的信噪比;对APD后脉冲概率的时间分布进行了研究,并进一步对AQC在更高器件过偏压下单光子探测中出现的问题进行了分析,提出了电路改进方案。结果表明,通过将AQC死区时间调整至45 ns,在相同单光子探测效率下,可将器件DCR减少至原先水平的1/4;通过有效抑制后脉冲和加快APD恢复速度,AQC可使器件展现出更加优越的探测性能。此研究为SiC APD在单光子探测中的应用提供了一定的参考。

Novel Logarithmic Active Pixel Sensor with High Dynamic Range and High Output Swing

The logarithmic response complementary metal oxide semiconductor （CMOS） image sensor provides a wide dynamic range, but its drawback is the lack of simple fixed pattern noise（FPN） cancellation scheme. Designed is a novel logarithmic active pixel sensor（APS） with high dynamic range and high output swing. Firstly, the operation principle of mixed-model APS is introduced. The pixel can work in three operation modes by choosing the proper control signals. Then, FPN sources of logarithmic APS are analyzed, and double-sampled technique is implemented to reduce FPN. Finally, according to the simulation results, layout is designed and has passed design rule check（DRC）, electronic rule eheck（ERC） and layout versus schematic（LVS） verifications, and the post-simulation results are basically in agreement with the simulation results. Dynamic range of the new logarithmic APS can reach about 140 dB; and the output swing is about 750 inV. Results show that by using double sampled technique, most FPN is eliminated and the dynamic range is enhanced.

离心式CO_2压缩机流量软测量研究

针对某石化公司离心式CO2压缩机四段出口动态流量准确测量困难的问题,引入软测量方法对动态流量进行测量,研究了基于支持向量机的软测量技术实现对流量的间接测量方法。提出了采用遗传算法和粒子群算法分别对支持向量机的参数进行优化,并将参数优化后的支持向量机得到体积流量软测量模型的预测效果与传统的交叉验证法参数优化的预测效果进行了对比,取得了良好的效果。