Internet Of Things Monitoring Research Articles

Monitoring System for the Construction of Arch Cover Method Subway Station Based on DT and IoT

Aiming at the problems of safety and monitoring beyond the existing experience in the construction of the subway stations with arch cover method in Dalian, China, combined with the real-time monitoring requirements of intelligent construction status, a multi-information construction monitoring system based on digital twin(DT) and Internet of Things(IoT) is proposed, and the digital twin 3D architecture is established. First, on the basis of the IoT monitoring experience of tunnel, the installation plan of the automatic monitoring device of the arch cover method subway station is clarified, and the sensor arrangement is carried out. Then, based on the Revit platform, the establishment of the main structure model of the station and the BIM parametric modeling technology of the sensors are realized, and the monitoring properties of the sensors are expanded. Finally, through the design of the BIM database and in the form of secondary development, a BIM-based construction information visualization monitoring system is established to realize the correlation between the sensor model and the monitoring data and achieve the effect of information visualization query and color change early warning. The system was initially applied at Shikui Road Station of Dalian Metro Line 5 and achieved good results. The system can intuitively reproduce and accurately describe the subway station construction status, which provides an advanced technical means for the informatization and visualization management of the construction of arch cover method subway stations.

Internet of Things (IoT Devices)-A Literature Review

Moving into the future world, life will be getting more easier and easier because of internet of things (IOT). Nowadays with increased need for surveillance, monitoring and data collection IOT has become more important. Today almost all devices are equipped with sensors and are controlled by controllers such as from cars to vacuum cleaners, rockets to Vernier calipers, air conditioners to water pumps. By embedding intelligence in everyday objects, they turned into smart devices and can be controlled from anywhere in the world. This paper discusses about internet of things and its advantages and disadvantages. It discusses the applications of IOT in various fields such as city, agriculture, remote monitoring, smart street light, etc. This paper also tells about the history of IOT.

Information model of low-voltage distribution IoT monitoring terminal based on IEC 61850

Abstract Low-voltage distribution lines lack efficient monitoring. With the massive proliferation of distributed energy resource supply, it is necessary to establish an effective monitoring system for low-voltage distribution lines to ensure the electrical safety and continuity of power supply services. This paper proposes monitoring system for low-voltage distribution lines based on the Internet of things (IoT) technology. An IoT based monitoring system contains a large number of low-voltage monitoring terminals, different manufacturers, and different types of terminal equipment to solve the interconnection problem of information interaction. This paper first analyzes the terminal functional communication requirements based on IEC 61850 standards. Further, the information models required by the electrical volume collection and non-electric quantity collection functions are studied. The information modeling for different types of monitoring terminal equipment is presented and thus provide the configuration suggestions. The monitoring terminal based on the information model developed in this paper is applied in a university campus to realize the monitoring of low-voltage lines and distributed power supply.

The Dissemination and Evaluation of Campus Ideological and Political Public Opinion Based on Internet of Things Monitoring.

With the advent of the information age, the rapid development of Internet of Things technology makes monitoring methods more flexible and changeable. As an intelligent application, the development of the Internet of Things brings convenience to public opinion monitoring. However, at present, due to the high price of transmission equipment, inconvenient maintenance, information delay, and other unfavorable conditions, real-time and controllable public opinion monitoring cannot be carried out on a large scale, and there are still many deficiencies in campus ideological and political public opinion monitoring. We found an effective transmission method, explored the network energy saving, dig deep into the transmission function of the signal system, and reduced the interference and mutual influence of various transmission accessories. In the application of the Internet of Things, the network public opinion is remotely monitored, the campus public opinion information is mastered, and its dissemination and development orientation are controlled. The exploration and research of online public opinion monitoring are in line with the goal of smart campus, and its theoretical development is constantly enriched.

DS-SWIPT: Secure Communication with Wireless Power Transfer for Internet of Things

Internet of Things (IoT) is promptly spreading and reaching a series of domains, including many industrial applications designed for monitoring purposes. In such networks, sensitive information is being collected and transmitted by IoT devices with limited resources, which leads energy efficiency and cybersecurity to become critical. Therefore, this paper proposes a novel approach for wireless communications and power for IoT monitoring applications with the aim of achieving energy efficiency and security. The proposed solution combines the advantages of Simultaneous Wireless Information and Power Transfer (SWIPT) for wireless power transfer to remote IoT devices and Direct Sequence Spread Spectrum (DSSS) for data confidentiality. The proposed DS-SWIPT is a security improvement over the original SWIPT. Simulation results show that the proposed DS-SWIPT can achieve energy efficiency along with acceptable data confidentiality.

Smart Sustainable Water Monitoring System via Internet of Things (IoT) for Water Retention Pond UiTM Cawangan Johor, Kampus Pasir Gudang

Water retention ponds developed in UiTM Pasir Gudang is used to accommodate the overflowed water from the campus facilities. Overflowed water is accumulated into this water retention pond and will flow to other water sources. Water from the water retentionpond has potential to contaminate other water sources as well as the environment. To maintain the water retention pond, a sustainable water monitoring system with an integration of internet of things (IoT) technology is designed and implemented. A fully developed integrated IoT monitoring system is presented in this research paper. The developedsystem will assess the water parameter such as pH and water temperature as well as water quality to serve as the water health indicator. This system includes a pH sensor, temperature sensor, rain sensor, sustainable power supply, wireless frequency data transmission module, and IoT data acquisition system in the base station. After the water data process has been performed and verified, the authorities will be notified of the unhealthy water condition. The developed system also allows any person or authority to monitor the water quality in that environment from anywhere.As a result of the collected data for water data parameters, the developed system provides an efficient water parameter monitoring system.Thus, early actions can be taken to reduce any harmful effects to the environment due to poor intervention.

Comprehensive survey of IoT based arduino applications in healthcare monitoring

The Internet of Things (IoT) enables a range of applications in the area of information technology, one of which is linked and smart health care. A successful Monitoring patients' health state in real time through an IoT healthcare system is the goal, to avert critical patient scenarios, and to enhance patient quality of life via smart IoT settings. Additionally, healthcare expenses are reduced, and patient outcomes are improved. Edge devices (glucose monitors, ventilators, pacemakers) are common in IoT systems. etc.). We reviewed the essential methodologies and cutting-edge technology for remote patient monitoring in this paper, taking into consideration data privacy and security concerns. The primary emphasis of this study is on the many solutions suggested in healthcare for IoT in real-time remote patient monitoring, blockchain technology in healthcare, and data security.

Innovation and Entrepreneurship Strategies of Teachers and Students in Financial Colleges and Universities Under the Direction of Food Security.

This study aims to better promote the innovation and entrepreneurship of teachers and students in finance and economics colleges and universities in terms of food security. Based on the relevant theories such as food security, innovation and entrepreneurship, the questionnaire was used to investigate the issues related to food security of teachers and students in colleges and universities. Next, the Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) analysis method was introduced to evaluate the safety metrics of the response subsystem. Finally, Internet of Things (IoT) monitoring technology was applied to grain growth and sales. The research results show that college teachers and students have a disjointed cognition of food security as important talents in innovation and entrepreneurship. After the TOPSIS analysis method is used to study, when college teachers and students choose to start a business in food security, they must pay attention to the changes in economic factors. The IoT monitoring technology is applied to grain growth and sales, and the monitoring technology of the IoT could reduce the mortality rate of corn seedlings to 3.59%. The mortality rate of seedlings is much higher than that of farmers relying on their own experience to grow corn. Therefore, this has great reference significance for the innovation and entrepreneurship development of college teachers and students in food security at this stage.

An Adaptive LoRaWAN MAC Protocol for Event Detection Applications

In recent years, the Internet of Things (IoT) is growing rapidly and gaining ground in a variety of fields. Such fields are environmental disasters, such as forest fires, that are becoming more common because of the environmental crisis and there is a need to properly manage them. Therefore, utilizing IoT for event detection and monitoring is an effective solution. A technique for monitoring such events over a large area is proposed in this research. This work makes use of the Long-Range Wide Area Network (LoRaWAN) protocol, which is capable to connect low-power devices distributed on large geographical areas. A learning-automata-based hybrid MAC model is suggested to reduce the transmission delay, when a small part of the network produces event packets stemming from an event occurrence that is related to environmental monitoring applications, such as events related to forest fires. The proposed hybrid MAC is evaluated via simulation, which indicates that it achieves significantly higher performance in terms of packet delay, when compared to traditional LoRaWAN schemes.

Toward a Brain-Computer Interface- and Internet of Things-Based Smart Ward Collaborative System Using Hybrid Signals.

This study proposes a brain-computer interface (BCI)- and Internet of Things (IoT)-based smart ward collaborative system using hybrid signals. The system is divided into hybrid asynchronous electroencephalography (EEG)-, electrooculography (EOG)- and gyro-based BCI control system and an IoT monitoring and management system. The hybrid BCI control system proposes a GUI paradigm with cursor movement. The user uses the gyro to control the cursor area selection and uses blink-related EOG to control the cursor click. Meanwhile, the attention-related EEG signals are classified based on a support-vector machine (SVM) to make the final judgment. The judgment of the cursor area and the judgment of the attention state are reduced, thereby reducing the false operation rate in the hybrid BCI system. The accuracy in the hybrid BCI control system was 96.65 ± 1.44%, and the false operation rate and command response time were 0.89 ± 0.42 events/min and 2.65 ± 0.48 s, respectively. These results show the application potential of the hybrid BCI control system in daily tasks. In addition, we develop an architecture to connect intelligent things in a smart ward based on narrowband Internet of Things (NB-IoT) technology. The results demonstrate that our system provides superior communication transmission quality.

Developing an agent-based platform to monitor intelligent buildings

In recent times, significant advancements have been evidenced in efforts to enhance connectivity and security within intelligent buildings (IBs). An IB is a contemporary structure that leverages state-of-the-art computer technologies to autonomously control the environmental conditions within a building to enhance occupants’ comfort, safety, work efficiency, and wellbeing while also ensuring optimal energy consumption. In the access aspect of a telecommunication network for IBs, the Main Distribution Frame (MDF) is in the central office. Intermediate Distribution Frames (IDFs) act as the isolation points for additional troubleshooting and further distribute the lines. The MDF is essentially a circuit switch that is typically operated through manual intervention because requests to establish or remove connections are sporadic and occasional. This can be tackled by utilizing Agent Based Systems (ABS) and Internet of Things (IoT) monitoring systems to develop a more holistic perspective of the process by which IDFs and MDF rooms are maintained. Furthermore, it will generate a process overview if we eradicate the process of physically checking a room that is currently used for IoT monitoring. In this research, a case study is presented to determine the feasibility of developing an IoT monitoring system. Currently, the monitoring applied in the case study is long, and over 40% of the equipment has maintenance failures. Distributed simulation of ABS is used to simulate the use of IoT for this project. Its data forecast can be very useful in determining the appropriate actions to improve the process of IDF and MDF and operational cost.

A distributed pavement monitoring system based on Internet of Things

Pavement is an important part of transportation infrastructure. In order to maintain pavement before the damage and improve the service quality, it is necessary to develop an intelligent and durable pavement information monitoring system. However, the pavement dynamic response monitoring is highly costly, easily obsolete and statistically redundant. The emergence of the Internet of Things (IoT) technology promises to change that. In this paper, an architecture of a distributed road IoT monitoring system is proposed, which has an acquisition layer, a preprocessing layer, a processing layer, an interaction layer, an energy layer and a network layer. Then, a prototype wireless pavement vibration monitoring system based on the IoT is developed, which consists of a number of wireless sensing nodes, a gateway, a remote server and a browser. Finally, data preprocessing, wireless communication, time synchronization, data processing and visualization, which represent the key to an effective system, are tested and discussed. The prototype wireless pavement vibration monitoring system provides a viable scheme for upgrading the IoT system and its application in the road infrastructures. In the future, any smart road will have an IoT wireless monitoring system to monitor the traffic, environment, and pavement information, which help enable traffic guidance, signal control, danger warning, scientific maintenance decision-making.

Design of IoT Monitoring System Based on LoRaWAN Architecture for Smart Green House

The application of smart agriculture as an applied innovation in overcoming uncertainty over natural conditions and supporting national food security. The utilization of smart agriculture with the Internet of Things (IoT) approach can spur increased added value, competitiveness, and commercial benefits for national food products. In this paper, we proposed a low-cost, modular, and Long-Range Wide-Area Network (LoRaWAN) monitor and collect the environmental data (air temperature and humidity) related to the growth in the smart greenhouse over a while. The proposed architecture has been evaluated on a real farm on a lab scale with RSSI -118 and SNR for 2% for 1000m. A web-based visualization tool for the collected data is also presented to validate the LoRaWAN architecture.

Open-source IoT monitoring system of a shallow geothermal system for heating and cooling year-round in Korea

We developed a geothermal monitoring system with an open-source Internet of Things (IoT) system. The study's objective is to achieve an economical alternative solution to the expensive commercial data loggers, local PC-based control, data storage limitation, the number of sensor connections, and secure data transmission over the Internet in a decentralized renewable energy system. The developed system consists of hardware and software customized with open-source support that helps resolve the conventional limitations that the commercial system inherently has. We have applied the system to a geothermal energy system deployed at a residential care facility for the elderly in Chuncheon, South Korea. The proposed system enabled us to acquire the data of temperature and fluid flow in real-time and for a prolonged period (i.e., years) at an affordable price compared to installing a conventional data-acquisition system. The real-time multi-year-long data helped confirm seasonality in heating and cooling. We can also apply the same proposed system to the other renewable energy systems monitoring temperature, pressure, wind speed, displacement, noise, seismicity, etc.

Monitoring and Predictive Maintenance of Centrifugal Pumps Based on Smart Sensors.

Centrifugal pumps have a wide range of applications in industrial and municipal water affairs. During the use of centrifugal pumps, failures such as bearing wear, blade damage, impeller imbalance, shaft misalignment, cavitation, water hammer, etc., often occur. It is of great importance to use smart sensors and digital Internet of Things (IoT) systems to monitor the real-time operating status of pumps and predict potential failures for achieving predictive maintenance of pumps and improving the intelligence level of machine health management. Firstly, the common fault forms of centrifugal pumps and the characteristics of vibration signals when a fault occurs are introduced. Secondly, the centrifugal pump monitoring IoT system is designed. The system is mainly composed of wireless sensors, wired sensors, data collectors, and cloud servers. Then, the microelectromechanical system (MEMS) chip is used to design a wireless vibration temperature integrated sensor, a wired vibration temperature integrated sensor, and a data collector to monitor the running state of the pump. The designed wireless sensor communicates with the server through Narrow Band Internet of Things (NB-IoT). The output of the wired sensor is connected to the data collector, and the designed collector can communicate with the server through 4G communication. Through cloud-side collaboration, real-time monitoring of the running status of centrifugal pumps and intelligent diagnosis of centrifugal pump faults are realized. Finally, on-site testing and application verification of the system was conducted. The test results show that the designed sensors and sensor application system can make good use of the centrifugal pump failure mechanism to automatically diagnose equipment failures. Moreover, the diagnostic accuracy rate is above 85% by using the method of wired sensor and collector. As a low-cost and easy-to-implement solution, wireless sensors can also monitor gradual failures well. The research on the sensors and pump monitoring system provides feasible methods and an effective means for the application of centrifugal pump health management and predictive maintenance.

Geothermal electricity generator using thermoelectric module for IoT monitoring

We propose a power generation system for IoT monitoring, using thermoelectric generator (TEG) modules and geothermal heat sources. Moreover, optimal conditions to operate the system for a hot spring in Thailand were investigated as a case study, i.e., feasibility study for utilization of geothermal energy as renewable energy. The aggregated TEG module was installed in the heat transfer channel soaked into a hot water bath. The generated power was used to supply the Internet of things (IoT) system for hot-spring monitoring. The IoT system was connected to sensors of temperature, humidity, and sulfur dioxide (SO2) to monitor and collect the information of the hot spring. The information can be monitored on mobile phones via the application. Twenty TEG modules were installed in the heat transfer channel. The heat sinks were used to transfer the heat while soaking into the hot water bath. By using the IoT system, data of the hot-spring monitoring was collected on cloud backup. The results show that the power outputs increase relating to the increase of the temperature gradient. The correlations between the power output and the hot water bathing temperatures were reported. The IoT system can collect information of hot-spring monitoring properly. It can be suggested from these features that energy recovery from the hot spring using TEG could be a potential source of renewable energy for the IoT system.

IoT and Blockchain-Based Mask Surveillance System for COVID-19 Prevention Using Deep Learning

On the edge of the worldwide public health crisis, the COVID-19 disease has become a serious headache for its destructive nature on humanity worldwide. Wearing a facial mask can be an effective possible solution to mitigate the spreading of the virus and reduce the death rate. Thus, wearing a face mask in public places such as shopping malls, hotels, restaurants, homes, and offices needs to be enforced. This research work comes up with a solution of mask surveillance system utilizing the mechanism of modern computations like Deep Learning (DL), Internet of things (IoT), and Blockchain. The absence or displacement of the mask will be identified with a raspberry pi, a camera module, and the operations of DL and Machine Learning (ML). The detected information will be sent to the cloud server with the mechanism of IoT for real-time data monitoring. The proposed model also includes a Blockchain-based architecture to secure the transactions of mask detection and create efficient data security, monitoring, and storage from intruders. This research further includes an IoT-based mask detection scheme with signal bulbs, alarms, and notifications in the smartphone. To find the efficacy of the proposed method, a set of experiments has been enumerated and interpreted. This research work finds the highest accuracy of 99.95% in the detection and classification of facial masks. Some related experiments with IoT and Block-chain-based integration have also been performed and calculated the corresponding experimental data accordingly. A System Usability Scale (SUS) has been accomplished to check the satisfaction level of use and found the SUS score of 77%. Further, a comparison among existing solutions on three emergent technologies is included to track the significance of the proposed scheme. However, the proposed system can be an efficient mask surveillance system for COVID-19 and workable in real-time mask detection and classification.

FRAMEWORK FOR TOUCHLESS PATIENT MONITORING SYSTEM INTEGRATING ULTRA-WIDEBAND RADAR AND INTERNET OF THINGS FOR COVID-19 PATIENTS

Effective Health monitoring and patient monitoring system is an inevitable need for the present world with the rapid increase of affected people due to various chronic diseases. Monitoring various health parameters like body temperature, blood pressure, heart beat, oxygen level and sugar level is very important to be proactive against chronic and pandemic diseases. Internet of Things (IoT) has gained a great interest in the health care sector through different wearable sensor devices. Monitoring the patients is a great challenge during pandemic diseases since the doctors and other medical practitioners were exposed to risk. This paper presents a novel touchless health and patient monitoring system (THPMS) embedding ultra-wide band (UWB) and IoT technologies for effective monitoring of COVID-19 patients. The IoT module is specifically designed for health monitoring whereas as UWB radar is designated for effective touchless patient monitoring. The IoT module comprises of temperature sensor, heart beat sensor and pulse oximeter which senses and stores the information in internet cloud which can be accessed through mobile and web applications. The UWB radar is integrated with the system for touchless patient monitoring. The proposed system also embedded with heath assisting module where it allows the person to interact with the doctors after receiving their health parameters through the mobile bot application termed as IOT FITBOT. The proposed system offers health monitoring through IoT module, patient monitoring through UWB radar and health assisting through IOT FITBOT application. Mobile application and WEB based graphical user interface (GUI) is developed to receive the

Drone-based AI/IoT Framework for Monitoring, Tracking and Fighting Pandemics

Since World Health Organization (WHO) has declared the Coronavirus disease (COVID-19) a global pandemic, the world has changed. All life's fields and daily habits have moved to adapt to this new situation. According to WHO, the probability of such virus pandemics in the future is high, and recommends preparing for worse situations. To this end, this work provides a framework for monitoring, tracking, and fighting COVID-19 and future pandemics. The proposed framework deploys unmanned aerial vehicles (UAVs), e.g.; quadcopter and drone, integrated with artificial intelligence (AI) and Internet of Things (IoT) to monitor and fight COVID-19. It consists of two main systems; AI/IoT for COVID-19 monitoring and drone-based IoT system for sterilizing. The two systems are integrated with the IoT paradigm and the developed algorithms are implemented on distributed fog units connected to the IoT network and controlled by software-defined networking (SDN). The proposed work is built based on a thermal camera mounted in a face-shield, or on a helmet that can be used by people during pandemics. The detected images, thermal images, are processed by the developed AI algorithm that is built based on the convolutional neural network (CNN). The drone system can be called, by the IoT system connected to the helmet, once infected cases are detected. The drone is used for sterilizing the area that contains multiple infected people. The proposed framework employs a single centralized SDN controller to control the network operations. The developed system is experimentally evaluated, and the results are introduced. Results indicate that the developed framework provides a novel, efficient scheme for monitoring and fighting COVID-19 and other future pandemics.

Multi-Path Service Function Chaining for Mobile Surveillance of Animal Husbandry

Animal husbandry is the pillar industry in some ethnic areas of China. However, the communication/networking infrastructure in these areas is often underdeveloped, thus the difficulty in centralized management, and challenges for the effective monitoring. Considering the dynamics of the field monitoring environment, as well as the diversity and mobility of monitoring targets, traditional WSN (Wireless Sensor Networks) or IoT (Internet of Things) is difficult to meet the surveillance needs. Mobile surveillance that features the collaboration of various functions (camera, sensing, image recognition, etc.) deployed on mobile devices is desirable in a volatile wireless environment. This paper proposes the service function chaining for mobile surveillance of animal husbandry, which orchestrates multi-path multi-function (MPMF) chains to help mobile devices to collaborate in complex surveillance tasks, provide backup chains in case the primary service function chain fails due to mobility, signal strength, obstacle, etc., and make up for the defects of difficult deployment of monitoring facilities in ethnic areas. MPMF algorithm models both mobile devices and various functions deployed on them as abstract graph nodes, so that chains that are required to traverse various functions and hosting mobile devices can be orchestrated in a single graph-based query through modified and adapted Dijkstra-like algorithms, with their cost ordered automatically. Experiment results show that the proposed MPMF algorithm finds multiple least-costly chains that traverse demanded functions in a timely fashion on Raspberry Pi-equipped mobile devices.