Sensor System For Monitoring Research Articles

Infrared-based sensor system for contactless monitoring of wetness and ice

Abstract. In order to differentiate between a wet and a dry road surface, the water film height should be measured by using an infrared-based sensor system. By means of different wavelengths, it is also possible to distinguish between ice and water. In this article, a sensor system for the determination of the physical state of water on different surfaces using infrared LEDs and one photodiode is presented. This shall serve as a basis for the calculation of the road condition. Here, emitted and reflected signals of five different infrared emitters are acquired with an infrared receiver. In commercial sensors this method (operating with one emitter) is used to determine a distance. At a constant distance, different intensities of the reflected signal are measured depending on the colour and texture of the surface. Similar sensor systems work with a broadband light, usually a halogen lamp, and several photodiodes. This type of sensor system is more cost-intensive and not robust enough for the desired application. The transmission spectrum of water shows that light is absorbed at a wavelength of 900 nm and strongly at a wavelength of about 1.4–1.5 µm. From the absorption spectrum of ice, it can be concluded that the wavelengths up to 1.4 µm are absorbed less than the wavelength at 1.5 µm. Therefore, the intensity depends not only on the material surface, but also on the wavelength of the transmitting and receiving diode. In order to distinguish between ice and water, the intensities of the light at the wavelengths 1.45 and 1.55 µm are compared, which is shown in this article by the measurements. In ice, the infrared light is more strongly absorbed at 1.55 µm.

Soil moisture and matric potential – an open field comparison of sensor systems

Abstract. Soil water content and matric potential are central hydrological state variables. A large variety of automated probes and sensor systems for state monitoring exist and are frequently applied. Most applications solely rely on the calibration by the manufacturers. Until now, there has been no commonly agreed-upon calibration procedure. Moreover, several opinions about the capabilities and reliabilities of specific sensing methods or sensor systems exist and compete. A consortium of several institutions conducted a comparison study of currently available sensor systems for soil water content and matric potential under field conditions. All probes were installed at 0.2 m b.s. (metres below surface), following best-practice procedures. We present the set-up and the recorded data of 58 probes of 15 different systems measuring soil moisture and 50 further probes of 14 different systems for matric potential. We briefly discuss the limited coherence of the measurements in a cross-correlation analysis. The measuring campaign was conducted during the growing period of 2016. The monitoring data, results from pedophysical analyses of the soil and laboratory reference measurements for calibration are published in Jackisch et al. (2018, https://doi.org/10.1594/PANGAEA.892319).

In-Sewer Field-Evaluation of an Optical Fibre-Based Condition Monitoring System

A Fiber Bragg Grating (FBG) based monitoring system for continuous humidity and temperature measurement has been designed and evaluated experimentally in a sewer environment with high corrosion rates, humidity and the presence of gaseous hydrogen sulfide. The monitoring system has been designed specifically for field use, including packaging prepared for the harsh environment and the challenges of the operation. The system is battery powered and has hardware for controlling the interrogation equipment, power management, data logging and 4G connectivity. Results obtained show the long-term performance, over a 6-month period of non-stop monitoring of real-time data using the same probe. The data acquired was compared to the environmental data of temperature and precipitation for this period from the same location, which showed a good correlation between the expected and the measured data values. The data obtained point to the success of the optical fibre-based sensor system for monitoring in these harsh environments over long periods.

A data-driven approach for pipe deformation prediction based on soil properties and weather conditions

The health condition of infrastructure including water transmission and distribution mains has a great impact on the quality of human life. The performance of these water infrastructure is affected by the surrounding soil environment as well as the weather or climate changes. To investigate the structural response of water mains to varying soil movements, field data were collected with a sensor monitoring system. This included pipe wall strain in-situ soil water content, soil pressure, and temperature. Combined with weather factors, an automatic variable selection method, i.e., recursive feature elimination, was first applied to identify critical predictors contributing to pipe deformation. Then, a super learning algorithm was employed to characterize the relationship between pipe deformation and environmental factors. Both base and super learners were built to predict three types of pipe deformation which verified the adaptability of two modeling methods to different predictive models. Predictive performance was evaluated through R-squared, root-mean-square error, and mean absolute error values. The performance metrics demonstrate the advantage of the super learning algorithm in comparison with the baseline methods, especially its capability to further incorporate extra base learners and predictors in a more complex setting. This study shows that the pipe structure behavior could be successfully inferred from surrounding soil properties and weather conditions.

Distribution of fishing vessels derived Visible Infrared Imaging Radiometer Suite (VIIRS) Sensor and Vessel Monitoring System (VMS) in the Java Sea

We analyzed the distribution of Purse seine fishing vessels using fishing lamps derived from the Day/Night Band Visible Infrared Imaging Radiometer Suite (DNB-VIIRS) sensor and Vessels Monitoring System (VMS) platform in the Java Sea. The data of fishing vessel distribution derived the DNB-VIIRS sensor and VMS platform was provided by NOAA Center for Environment Information and Global Fishing Watch respectively. The intensity of lights during the fishing operation was measured by a lux meter. The fishing vessel types that used light during fishing operations were small (< 15 units lamps) and large vessels (>15-unit lamps). The intensity of light in the big vessels (> 2,000 Lux) was higher than the small vessels (< 2,000 Lux). The average number of fishing vessels operating during the Southeast monsoon were more than those of the Northwest monsoon. The distribution of fishing vessels derived from the DNB-VIIRS sensor has a similar pattern with the VMS platform. Generally, the fishing vessels are concentrated along the southern coast of Borneo but in the Northwest monsoon shift towards the northwest of Java approaching the island of Sumatra.

Compressed Sensing for Energy Conservation Pavement Temperature Compression on Epave

Monitoring the road condition has gain significant importance in last few years. Among existing road monitoring technologies, wireless sensor network (WSN) is favored by researchers because of its low cost and flexibility in deployment. Specifically, it can collect road condition data spontaneously and transmit the information to a fusion center that can determine the damage level or status of the road surface. However, there is a big challenge preventing the wide deployment of WSN that the sensor nodes can only survive for a limited time in practice. It is because majority of the power has been spent on the continuous wireless transmission of the extensive road data to the fusion center. In this study, we propose a low-power temperature data transmission scheme based on compressed sensing in combination with self-powered road surface wireless monitoring sensor system to realize data sparseness and compression and reduce system power consumption. Experimental results show that the compressed data can reduce the power consumption requirement by 50.78% under the allowable reconstruction error by comparison with the existing approaches.

Bio-Intelligent Selective Laser Melting System based on Convolutional Neural Networks for In-Process Fault Identification

This research work focuses on the development of a bio-intelligent additive manufacturing system based on Selective Laser Melting (SLM) technology in the framework of the Biological Transformation in Manufacturing. With the objective to provide the SLM system with cognition, decision making and self-learning capabilities inspired by human intelligence and cognitive skills, a machine learning approach using convolutional neural networks for in-process fault identification based on automatic image processing is presented. An in-process sensor monitoring system based on a camera installed on the SLM machine tool is employed to acquire images of the scanned layers with the final aim to timely identify possible faults and realize an adaptive layer-by-layer control loop in which the process is self-adjusted based on learning.

Dps-MuSyQ: A Distributed Parallel Processing System for Multi-Source Data Synergized Quantitative Remote Sensing Products Producing

With the development of earth observation technologies and the construction of earth observation systems, an increasing amount of remote sensing data are being obtained. These provide the datasets required for research on remote sensing monitoring across large areas. To compensate for the shortcomings of global and large-area temporal monitoring data, synergized computing using multi-source remote sensing data can improve the accuracy and temporal resolution of remote sensing monitoring. However, remote sensing data are drawn from multiple sources and multiple scales, and have a complex structure and large volume; in addition, the nested system architecture of multi-source synergized remote sensing products makes the design of large-scale multi-source synergized remote sensing monitoring systems difficult. In this paper, we describe the design and implementation of a distributed parallel processing system for multi-source data synergized quantitative remote sensing based on a distributed cluster platform. The system integrates the algorithms normalizing more than 30 kinds of data sources and producing 40 quantitative remote sensing products. The system also connects a number of centers for satellite data, serves for several applications, and implements dynamic expansion integration for highly efficient quantitative remote sensing products. The system has produced approximately 50 TB of quantitative remote sensing products, and the application of these data to agriculture, forestry, the environment, and water conservation has resulted in very positive effects.

Design of Internet of Things (IoT) and Android Based Low Cost Health Monitoring Embedded System Wearable Sensor for Measuring SpO2, Heart Rate and Body Temperature Simultaneously

In this paper, an implementation of affordable medical technology health monitoring sensor system is developed and demonstrated to measure blood saturation levels (SpO2), heart rate and body temperature simultaneously. The embedded system is based on Arduino platform due to reliability and plug and play capability. The proposed pulse oximetry sensor uses spectrophotometry to calculate the ratio of oxygenated hemoglobin to deoxygenated hemoglobin which then is used to calculate the percentage of oxygenated blood levels. The accuracy of pulse oximeter is enhanced using light emitting diodes driver circuits, sample and hold circuits thus that a variable baseline can be established for different skin tones including the finger width where the measurements are undertaken. The embedded sensor system is designed to monitor SpO2, heart rate and body temperature and display the obtained results on an LCD. The measured vitals are also transmitted via Bluetooth module to Android mobile, and using Wi-Fi module to the internet, forming internet of things platform for the designed embedded system of sensors. The low cost embedded sensor system reported in this study can be used to monitor key health parameters of patients in hospitals or at home. The proposed affordable medical technology sensor system can be used as wearable wireless sensor which can be used as a plug and play sensor with Arduino to monitor human key health parameters. The measured health parameters are compared with commercially available ChoiceMMed pulse oximeter and a maximum deviation of 2% is observed which demonstrates that the proposed sensor device is highly accurate.

Design of sensor system for air pollution and human vital monitoring for connected cyclists

This study addresses the design of smart sensor system aided bicycle that can be exploited as a platform for the acquisition of real-time data. In particular, in this work, the authors address the pressing issues like air pollution monitoring and health monitoring by using sensors that were seen as limitations in the already existing smart e-bike monitoring system. The sensor system presented in this study is capable of monitoring parameters such as location, heart rate of the rider and air quality levels in real-time. The data thus collected is fed into Thingspeak, an open Internet of Things platform powered by Matlab. The data is then visually represented in an Android application for riders to view and analyse the monitored parameters. The Android application designed for the system assists the user with location tracking, pollution mapping and health monitoring. Furthermore, security is also considered in this work which is addressed with the help of a fingerprint sensor and a global system for mobile/global positioning system module to alert the user in case of system theft. The system attached to the bicycle can be implemented on a large scale as a fleet/bike sharing system in order to map the pollution of an entire city with the help of IoT, thus aiding the development of greenfield smart city and additionally monitoring the vitals of the user riding the bicycle leading to intelligent transportation system. This study details the design and implementation of the hardware and software, enlists the outcomes of the system and explores the future scope and development.

A Low-Power Sensitive Integrated Sensor System for Thermal Flow Monitoring

Thermal-based flow monitoring has found widespread applications due to its noncontact measurement, high sensitivity, low flow resistance, miniaturization, ease of integration, and low-power consumption. In this work, a low-cost and affordable inkjet-printed graphene-based thermal sensor is integrated with a low-power CMOS circuit for flow rate monitoring. The custom inkjet-printed sensor consists of a silver nanoparticle interdigitated pattern with a coating of graphene, all printed on a glossy photo-paper substrate. The sensor read-out circuit is an energy-efficient current-starved ring oscillator. The sensor current controls the bias current of a current-starved ring oscillator and modulates the output frequency. A driver circuit then transforms the output to a square wave pulse signal. The scheme is designed and fabricated using the 0.13- $\mu \text{m}$ standard CMOS process and occupies an area of 1.5 mm $\times1.7$ mm. Test results indicate that the prototype ring oscillator circuit consumes 19– $90~\mu \text{W}$ for an oscillation frequency variation of 517 kHz–6.45 MHz. The output frequency variation with sensor current shows linear performance with ${R}^{2} = 0.9966$ .

Wired Sensor Systems for Water Quality Monitoring

Water is an essential need and elixir of life. People all the world are fighting for their drinking water in order to keep it clean. No matter in what form it is rivers, lakes etc people have taken extreme measures to keep their water drinkable and useable for both humans and animals. Water is a significant characteristic asset without which no life can be envisioned. In any case, individuals misuse this real asset and cause wastage of water. We provide energy saving solution for monitoring the water quality. The proposed idea will build an IOT based sensor which monitors the pH, temperature, conductivity, dissolved oxygen, turbidity, bacteria, etc. present in the water collected. The sensors collect data and send it through a network. Then server will upload the data to the cloud. The remote water station will read the collected data and determine the quality of water. Henceforth, this application can be used on bigger scales, saves time and man-power.

Embedded Wireless Sensor Systems for Resin Flow Monitoring in Glass and Carbon Fiber Composites

The obtained data can be used for modeling the resin flow inside the composite, which is required for simulation and for speeding up the design of new parts. This paper presents a novel wireless sensor system that can be embedded in both glass and carbon fiber composites allowing for the first time to wirelessly measure pressure and temperature throughout the laminate during infusion, giving an insight into the process behavior. We suggest a system, which uses wireless data transmission that does not hurt the vacuum seal, even for sensors deeply embedded between conductive carbon fibers. The current sensor system gives an accurate pressure reading (mbar resolution) that provides information about the pressure gradient in the whole laminate. For carbon fibers, the sensors are soldered on a self-made, flexible, and 10 $\mu \text{m}$ -thick polyimide cable, which is resistant to high temperatures. This makes the system minimally invasive since only a $\mathbf {2}\,\,\mathbf {mm}\boldsymbol \times 2.5\,\,\mathbf {mm}$ system remains inside the laminate.

Arm-ECG Wireless Sensor System for Wearable Long-Term Surveillance of Heart Arrhythmias

This article presents the devising, development, prototyping and assessment of a wearable arm-ECG sensor system (WAMECG1) for long-term non-invasive heart rhythm monitoring, and functionalities for acquiring, storing, visualizing and transmitting high-quality far-field electrocardiographic signals. The system integrates the main building blocks present in a typical ECG monitoring device such as the skin surface electrodes, front-end amplifiers, analog and digital signal conditioning filters, flash memory and wireless communication capability. These are integrated into a comfortable, easy to wear, and ergonomically designed arm-band ECG sensor system which can acquire a bipolar ECG signal from the upper arm of the user over a period of 72 h. The small-amplitude bipolar arm-ECG signal is sensed by a reusable, long-lasting, Ag–AgCl based dry electrode pair, then digitized using a programmable sampling rate in the range of 125 to 500 Hz and transmitted via Wi-Fi. The prototype comparative performance assessment results showed a cross-correlation value of 99.7% and an error of less than 0.75% when compared to a reference high-resolution medical-grade ECG system. Also, the quality of the recorded far-field bipolar arm-ECG signal was validated in a pilot trial with volunteer subjects from within the research team, by wearing the prototype device while: (a) resting in a chair; and (b) doing minor physical activities. The R-peak detection average sensibilities were 99.66% and 94.64%, while the positive predictive values achieved 99.1% and 92.68%, respectively. Without using any additional algorithm for signal enhancement, the average signal-to-noise ratio (SNR) values were 21.71 and 18.25 for physical activity conditions (a) and (b) respectively. Therefore, the performance assessment results suggest that the wearable arm-band prototype device is a suitable, self-contained, unobtrusive platform for comfortable cardiac electrical activity and heart rhythm logging and monitoring.

Advanced Fiber Optic and Ultrasonic Sensor Systems for Structural Health Monitoring of Pipes in Nuclear Waste Sites

Abstract Nuclear waste sites across the United States and other countries store, transfer and vitrify nuclear waste. These sites often require transfer pipelines for high and low level radioactive wastes in the form of solids/slurries, fluids including chemicals. Since, these pipelines deal with harmful nuclear wastes, structural health monitoring is of utmost importance. Pipelines are continuously monitored to enhance the safety of the people and environment around the facilities. Monitoring may involve leak, crack detection and wear (in the form of corrosion or thinning). Current research builds on author's previous work on sensors for erosion and thermal monitoring in pipes and plates [1, 2, and 3]. Present work involves a) validation and monitoring of a novel advanced Fiber Optic Sensor System to detect cracks and leaks in carbon steel pipes and b) the use of Ultrasonic (UT) sensors to detect thinning in pipe sections due to erosion-corrosion using small coupons. The fiber optic sensors developed by CEL [4], are used in conducting engineering scale testing on an in-house designed and assembled erosion pipe flow loop. The loop consists of 2 and 3 inch straight and elbow sections of carbon steel replicating the pipelines at the sites. Three fiber optic sensors are placed at critical locations around the loop. The equipment also includes a communication box and a laptop device for data acquisition. The sensor system uses a combination of fiber optic and acoustic technologies to accurately identify the location of a pipeline leak or crack. Sensors capture the changes in pressure caused by the fluid/slurry flowing through the loop. A “zone” is defined as the distance between any two sensor points. When any two sensors simultaneously detect a leak, a determination can be made as to how far from each sensor the activity is occurring and “zero in” on the event. A number of zones may be linked together to manage vast expanses of pipeline. Sensors provide instantaneous event data to the hardware (the interrogator), and the interrogator may be located great distances from the actual pipeline in secure, environmentally protected areas. Multiple Interrogators may be linked together that are simultaneously streaming real-time data to the command and control software. Event notifications may then be managed from the customer's control room, or immediately “pushed” to a variety of mobile devices to alert personnel of the situation [5]. Additionally, Ultrasonic (UT) sensors are used for thickness measurements in pipes. The objective is to measure the wear in pipelines due to erosion-corrosion using small scale erosion coupons. These erosion coupons are made of carbon steel with ½ inch in diameter and 1 inch height. The method involves insertion of the coupons into holes drilled in the pipe sections of the erosion loop. This process ensures that the coupons are in contact with the flow stream and hence eroded in a minute scale over a period of time. The coupons have a slot for insertion of the sensors to measure the thickness in real-time when needed. Upon successful testing of the coupon and sensors, the method can be used to predict the erosion rates and hence the remaining useful life of the pipe sections without having to replace them unnecessarily. Hence, the present research conducts structural health monitoring of carbon steel pipes using fiber optic and UT sensors. The sensors have been validated and verified for their potential future deployment in the nuclear waste sites.

Fiber optic sensor systems for non-destructive monitoring of “smart buildings”

The article presents the solution of the actual problem of complex monitoring of external influence parameters for urban infrastructure facilities of a “smart” city. The main characteristics of fiber-optic sensors and their sensing systems are shown. Their advantages over traditional technologies for the development of monitoring directions in “smart” cities are indicated. Solutions using fiber-optic sensor networks based on quasi-distributed systems are presented.

Design and fabrication of cost-effective heart-rate pulse monitoring sensor system

A traditional approach of heart rate measurement has always meant that people must go to hospitals to examine the patient disease at Cardiologist and medical officer. Most people have difficult such as no transport and lazy to go to the hospital for the check-ups of their conditions heart rate. This is because, before have a treatment or medical check-up, they should do an appointment. Besides that, demands of works very high nowadays. People busy with their works until forget to do medical check-ups. Additionally, the available portable heart rate monitoring machine is costly to buy for all. In this research, we develop a system which can be accommodate for all while everyone can do their check up at home and do not waste their time by waiting for their turn in the hospital to do the medical check-ups. The prototype is built using low cost electronics components. The prototype can do a self-check-up before seeing a medical practitioner may reduce mortality rate due to the silent killer that is heart attacks.

Development and Pilot Installation of a Scalable Environmental Sensor Monitoring System for Freeze–Thaw Monitoring under Granular-Surfaced Roadways

The freeze–thaw cycle is one of the major sources of damage to granular-surfaced roadways, especially in areas where the timing of heavy agricultural traffic coincides with that of spring thawing. To help local roads agencies plan better for annual budgets and frost embargos, it is useful to be able to predict the frost depth and number of freeze–thaw cycles under a given roadway based on continually updated weather and soil data. Computational modeling can help in this regard, and may be conducted by collecting data on weather and the thermal and hydraulic properties of the soil, as well as soil temperature, moisture, and suction, and using the data directly in the analyses. In order to obtain accurate field data for model calibrations and predictions, an appropriate sensor network and data acquisition system must be carefully planned and installed. This article details the development and installation procedures for one such system of sensors for subgrade temperature, water content, and matric suction, and presents lessons learned throughout the process. Various issues are discussed relating to selection of the sensor and data acquisition system, laboratory and field checks, borehole sensor installation tools, and post-installation troubleshooting and monitoring. To ensure a successful installation beneath the granular roadway, laboratory and field trials were first performed. Salient details of a pilot installation in Hamilton County, IA are provided to guide others developing and scaling similar subgrade sensor systems.

Low-Cost Piezoelectric Transducer for Ceramic Grinding Monitoring

This paper presents a performance assessment of the low-cost thin-disk piezoelectric diaphragm (PZT) for the surface integrity monitoring in the grinding operation. PZT diaphragms are flexible, low-cost, and smart devices, making them promising for applications in manufacturing fields, such as in the grinding operation. To accomplish this, experimental grinding tests were carried out on workpieces of ceramic material covering from slight to severe machining conditions. A low-cost thin-disk PZT diaphragm was assessed, which was attached to the workpiece holder using a cyanoacrylate glue. In addition, a commercial and consolidated acoustic emission (AE) sensor was used as a baseline for comparative purpose. Likewise, the surface roughness measurements were performed after grinding each workpiece to support the sensor monitoring system. Feature extraction using frequency spectrum and time domain analysis were applied to the sensor signals by means of fast Fourier transform (FFT), digital bandpass filters, root mean square (RMS) value, and power deviation (DPO) metric. The results indicate a clear relationship between the thin-disk PZT diaphragm and the conventional AE sensor for surface integrity monitoring in grinding, which proves the effectiveness and reliability of an innovative sensing device for the present application.

Leach Protocol in Wireless Sensor Networks using Matlab

Today, at this age of intelligent technology, the intelligent have entered agriculture in a great way. The base of this study is WSN based irrigation system. In this work various problems in the irrigation system based on traditional wireless sensor networks. The flaw is related to the selection approach for CH (cluster head). The most important technologies are used in this work i.e. to develop an automatic and intelligent irrigation system. The use of a sensor monitoring system is an effective method to prevent interference and to improve efficiency. The CH election approach is modified by enhancing the list of network influencing factors. To sense the energy of the overall network, LEACH and IMPROVED LEACH protocol are compared to have a better and efficient network. MATLAB simulates and evaluates the performance of the communication system in terms of network life. The results of the simulation show the different amount of sensors initial energy in relation to the dead last node and the dead first node.