Research on a Comprehensive Monitoring System for Tunnel Operation based on the Internet of Things and Artificial Intelligence Identification Technology

This article proposes a comprehensive monitoring system for tunnel operation to address the risks associated with tunnel operations.These risks include safety control risks,increased traffic flow,extreme weather events,and movement of tectonic plates.The proposed system is based on the Internet of Things and artificial intelligence identification technology.The monitoring system will cover various aspects of tunnel operations,such as the slope of the entrance,the structural safety of the cave body,toxic and harmful gases that may appear during operation,excessively high and low-temperature humidity,poor illumination,water leakage or road water accumulation caused by extreme weather,combustion and smoke caused by fires,and more.The system will enable comprehensive monitoring and early warning of fire protection systems,accident vehicles,and overheating vehicles.This will effectively improve safety during tunnel operation.

Design of Intelligent Pension Online Monitoring System Under the Environment of Internet of Things

With the improvement of the degree of aging,the traditional pension model can no longer meet the growing needs of the elderly.Therefore,it is necessary to use the intelligent means of information technology to improve the level of pension services.This paper will integrate multi-sensor fusion technology,NB-IoT communication technology and cloud platform technology to develop and design a smart pension online monitoring system to realize real-time collection of human health and motion status information and realize monitoring platform management.In this system,STM32 microcontroller will be used as the main control module,and MAX30102,ADXL345 and DS18B20 sensors will be used to collect the heart rate,blood oxygen,displacement and body temperature of the human body in real time.On the one hand,the communication part is completed by the BC20 Internet of Things module.The data transmission between the terminal detection device and the cloud platform,on the other hand,the HC-42 Bluetooth module is used to complete the data communication with the mobile phone.The test results show that the system can collect and process data accurately in real time and maintain good communication with the cloud platform and mobile phone.The designed system has strong pertinence,easy operation,high reliability and broad development prospects.

A Systematic Review on the Internet of Medical Things:Techniques,Open Issues,and Future Directions

IoT usage in healthcare is one of the fastest growing domains all over the world which applies to every age group.Internet of Medical Things(IoMT)bridges the gap between the medical and IoT field where medical devices communicate with each other through a wireless communication network.Advancement in IoMT makes human lives easy and better.This paper provides a comprehensive detailed literature survey to investigate different IoMT-driven applications,methodologies,and techniques to ensure the sustainability of IoMT-driven systems.The limitations of existing IoMTframeworks are also analyzed concerning their applicability in real-time driven systems or applications.In addition to this,various issues(gaps),challenges,and needs in the context of such systems are highlighted.The purpose of this paper is to interpret a rigorous review concept related to IoMT and present significant contributions in the field across the research fraternity.Lastly,this paper discusses the opportunities and prospects of IoMT and discusses various open research problems.

Internet of Cultural Things: Current Research, Challenges and Opportunities

Driven by the visions of the Internet of Things(IoT),Artificial Intelligence(AI),and 5G communications,the Internet of Cultural Things(IoCT)realize the comprehensive interconnection among cultural products,cultural services,cultural resources,and cultural platforms,bringing individuals with richer humanistic experience,increasing economic benefits for the cultural sector,and promoting the development of cultural heritage protection and education.At present,IoCT has received widespread attention in both industry and academia.To explore new research opportunities and assist users in constructing suitable IoCT systems for specific applications,this survey provides a comprehensive overview of the IoCT components and key technologies.A comparison study of representative IoCT systems is presented according to their applicability.A general platform architecture of IoCT is proposed to link cultural objects with the internet and human.Finally,open issues for research challenges and future opportunities of IoCT are also studied in this paper.

Artificial Intelligence and Internet of Things Enabled Intelligent Framework for Active and Healthy Living

Obesity poses several challenges to healthcare and the well-being of individuals.It can be linked to several life-threatening diseases.Surgery is a viable option in some instances to reduce obesity-related risks and enable weight loss.State-of-the-art technologies have the potential for long-term benefits in post-surgery living.In this work,an Internet of Things(IoT)framework is proposed to effectively communicate the daily living data and exercise routine of surgery patients and patients with excessive weight.The proposed IoT framework aims to enable seamless communications from wearable sensors and body networks to the cloud to create an accurate profile of the patients.It also attempts to automate the data analysis and represent the facts about a patient.The IoT framework proposes a co-channel interference avoidance mechanism and the ability to communicate higher activity data with minimal impact on the bandwidth requirements of the system.The proposed IoT framework also benefits from machine learning based activity classification systems,with relatively high accuracy,which allow the communicated data to be translated into meaningful information.

Energy and Latency Optimization in Edge-Fog-Cloud Computing for the Internet of Medical Things

In this paper,the Internet ofMedical Things(IoMT)is identified as a promising solution,which integrates with the cloud computing environment to provide remote health monitoring solutions and improve the quality of service(QoS)in the healthcare sector.However,problems with the present architectural models such as those related to energy consumption,service latency,execution cost,and resource usage,remain a major concern for adopting IoMT applications.To address these problems,this work presents a four-tier IoMT-edge-fog-cloud architecture along with an optimization model formulated using Mixed Integer Linear Programming(MILP),with the objective of efficiently processing and placing IoMT applications in the edge-fog-cloud computing environment,while maintaining certain quality standards(e.g.,energy consumption,service latency,network utilization).A modeling environment is used to assess and validate the proposed model by considering different traffic loads and processing requirements.In comparison to the other existing models,the performance analysis of the proposed approach shows a maximum saving of 38%in energy consumption and a 73%reduction in service latency.The results also highlight that offloading the IoMT application to the edge and fog nodes compared to the cloud is highly dependent on the tradeoff between the network journey time saved vs.the extra power consumed by edge or fog resources.

Development of Wi-Fi Based Home Energy Monitoring System for Green Internet of Things

Green Internet of things （loT） has been heralded as the ＂next big thing＂ waiting to be realized in energy-efficient ubiquitous computing. Green IoT revolves around increased machine-to-machine communications and encompasses energy-efficient wireless embedded sensors and actuators that assist in monitoring and controlling home appliances. Energy efficiency in home applications can be achieved by better monitoring of the specific energy consumption by the appliances. There are many wireless standards that can be adopted for the design of such embedded devices in loT. These communication technologies cater to different requirements and are classified as the short-range and long-range ones. To select the best communication method, this paper surveys various loT communication technologies and discusses the advantages and disadvantages to develop an energy monitoring system. An IoT device based on the Wi-Fi technology system is developed and tested for usage in the home energy monitoring environment. The performance of this system is then evaluated by the measurement of power consumption metrics. In the efficient deep-sleep mode, the system saves up to 0.3 W per cycle with an average power dissipation of less than 0.1 W/s.

Application research of narrow band Internet of things buoy and surface hydrodynamics monitoring

This paper applies the narrow band Internet of things communication technology to develop a wireless network equipment and communication system, which can quickly set up a network with a radius of 100 km on water surface. A disposable micro buoy based on narrow-band Internet of things and Beidou positioning function is also developed and used to collect surface hydrodynamic data online. In addition, a web-based public service platform is designed for the analysis and visualization of the data collected by buoys. Combined with the satellite remote sensing data, the study carries a series of marine experiments and studies such as sediment deposition tracking and garbage floating tracking.

Internet of things-based health monitoring system for early detection of cardiovascular events during COVID-19 pandemic

The coronavirus disease 2019(COVID-19)has currently caused the mortality of millions of people around the world.Aside from the direct mortality from the COVID-19,the indirect effects of the pandemic have also led to an increase in the mortality rate of other non-COVID patients.Evidence indicates that novel COVID-19 pandemic has caused an inflation in acute cardiovascular mortality,which did not relate to COVID-19 infection.It has in fact increased the risk of death in cardiovascular disease(CVD)patients.For this purpose,it is dramatically inevitable to monitor CVD patients’vital signs and to detect abnormal events before the occurrence of any critical conditions resulted in death.Internet of things(IoT)and health monitoring sensors have improved the medical care systems by enabling latency-sensitive surveillance and computing of large amounts of patients’data.The major challenge being faced currently in this problem is its limited scalability and late detection of cardiovascular events in IoT-based computing environments.To this end,this paper proposes a novel framework to early detection of cardiovascular events based on a deep learning architecture in IoT environments.Experimental results showed that the proposed method was able to detect cardiovascular events with better performance(95.30%average sensitivity and 95.94%mean prediction values).

Design and Implementation of Environment Monitoring and Alarm System for Broiler Breeding Based on Internet of Things

Environment plays a vital role in the breeding process of broilers. In order to effectively monitor and control the breeding environment of broilers, a broiler breeding environment monitoring and alarm system based on internet of things is studied and established. The system adopts the narrow band internet of things communication technology, and can transmit the temperature, humidity, illumination and ammonia and other environ-mental data in the chicken house remotely through terminal collection unified interface device. Meantime, it realizes the control of fans, wet cur-tains, small windows and illumination in the chicken house by threshold method. The system software is designed and implemented by C#, SQL Server, WeX5 and other development tools, including platform terminal and enterprise terminal. Since its operation, the system is featured by stable state, reliable data and timely alarm, which solves the problem of unified control of different sensors and realizes the effective control of house envi-ronment.

Internet of Things for in Home Health Based Monitoring System:Modern Advances,Challenges and Future Directions

IOT has carried outimportant function in converting the traditional fitness care corporation.With developing call for in population,traditional healthcare structures have reached their outmost functionality in presenting sufficient and as plenty as mark offerings.The worldwide is handling devastating developingantique population disaster and the right want for assisted-dwelling environments is turning into inevitable for senior citizens.There furthermore a determination by means of the use of way of countrywide healthcare organizations to increase crucial manual for individualized,right blanketed care to prevent and manipulate excessive coronial situations.Many tech orientated packages related to HealthMonitoring have been delivered these days as taking advantage of net boom everywhere on globe,manner to improvements in cellular and in IOT generation.Such as optimized indoor networks insurance,community shape,and fairly-lowdevice fee performances,advanced tool reliability,low device energy consumption,and hundreds higher unusual common usual performance in network safety and privacy.Studies have highlighted fantastic advantages of integrating IOT with health care location and as era is improving the rate also cannot be that terrific of a problem.However,many challenges in this new paradigm shift notwithstanding the fact that exist,that need to be addressed.So the out most purpose of this research paper is 3 essential departments:First,evaluation of key elements that drove the adoption and boom of the Internet of factors based totally domestic some distance off monitoring;Second,present fashionable improvement of IOT in home a long manner off monitoring shape and key building gadgets;Third,communicate future very last effects and distinct guidelines of such type a long way off monitoring packages going ahead.Such Research is a wonderful manner in advance now not outstanding in IOT Terminology but in standard fitness care location.

GraphSTGAN:Situation understanding network of slow-fast high maneuvering targets for maritime monitor services of IoT data

With the rapid growth of the maritime Internet of Things(IoT)devices for Maritime Monitor Services(MMS),maritime traffic controllers could not handle a massive amount of data in time.For unmanned MMS,one of the key technologies is situation understanding.However,the presence of slow-fast high maneuvering targets and track breakages due to radar blind zones make modeling the dynamics of marine multi-agents difficult,and pose significant challenges to maritime situation understanding.In order to comprehend the situation accurately and thus offer unmanned MMS,it is crucial to model the complex dynamics of multi-agents using IoT big data.Nevertheless,previous methods typically rely on complex assumptions,are plagued by unstructured data,and disregard the interactions between multiple agents and the spatial-temporal correlations.A deep learning model,Graph Spatial-Temporal Generative Adversarial Network(GraphSTGAN),is proposed in this paper,which uses graph neural network to model unstructured data and uses STGAN to learn the spatial-temporal dependencies and interactions.Extensive experiments show the effectiveness and robustness of the proposed method.

Development of Long-Range,Low-Powered and Smart IoT Device for Detecting Illegal Logging in Forests

Forests promote the conservation of biodiversity and also play a crucial role in safeguarding theenvironment against erosion,landslides,and climate change.However,illegal logging remains a significant threatworldwide,necessitating the development of automatic logging detection systems in forests.This paper proposesthe use of long-range,low-powered,and smart Internet of Things(IoT)nodes to enhance forest monitoringcapabilities.The research framework involves developing IoT devices for forest sound classification andtransmitting each node’s status to a gateway at the forest base station,which further sends the obtained datathrough cellular connectivity to a cloud server.The key issues addressed in this work include sensor and boardselection,Machine Learning(ML)model development for audio classification,TinyML implementation on amicrocontroller,choice of communication protocol,gateway selection,and power consumption optimization.Unlike the existing solutions,the developed node prototype uses an array of two microphone sensors forredundancy,and an ensemble network consisting of Long Short-Term Memory(LSTM)and ConvolutionalNeural Network(CNN)models for improved classification accuracy.The model outperforms LSTM and CNNmodels when used independently and also gave 88%accuracy after quantization.Notably,this solutiondemonstrates cost efficiency and high potential for scalability.

Application research on three-dimensional virtual mine in the framework of internet of things

Based on the information system characteristics of mine, proposed network architecture design of the mine property. And in this framework based on the design of three-dimensional virtual mine described the application of intelligent management platform. Three-dimensional virtual underground mine that shows the situation, the core application is through remote monitoring system of information exchange between devices （material object communication）. Internet of things in the framework of mining three-dimensional virtual reconstruction of mine. On coal mine safety in the production process of human, machine and environment, control elements and their harmony and unity. 3D virtual mine management platform integrates personnel positioning, dust control, gas monitoring, roof pressure monitoring, fan-line monitoring and other subsystems. Platform through the underground mine sensing equipment to conduct various types of monitoring data integration, through the transport layer device to transmit the information to the application layer intelligence processing software platform, the system automatically handles the operational status of each subsystem and the need for safe production under the proper introduction of human factors deal with special event. 3D virtual mine management platform to mining, excavation, transport, ventilation and other safety information quickly and accurately transmitted to the ground operation control center. Underground for the first time on the linkage between systems in case of emergencies, to provide safety for management decision support.

Analysis of identifiers in IoT platforms

The Internet of Things(IoT)provides new opportunities for different IoT platforms connecting various devices together.The need to identify those devices is the foremost important to perform any kind of operation.Many organizations and standard bodies that provide specifications and frameworks for the IoT currently have their own identification mechanisms.Some existing industrial identification mechanisms can also be used in the IoT.There is no common Identification Scheme(IS)for the IoT as yet,because of the political and commercial differences amongst the standard bodies.The unavailability of a unified IS method makes the inter-working among IoT platforms challenging.This paper analyses and compares ISs used by several selected IoT platforms.This work will help in understanding the need for a common identification mechanism to provide inter-working among different IoT platforms.

Monitoring and Detection of Wind Turbine Vibration with KNN-Algorithm

Maintenance for wind turbines has been transformed using supervised machine learning techniques. This method of automatic and autonomous learning can identify, monitor, and detect electrical and mechanical components of wind turbines and predict, detect, and anticipate their degeneration. Using a machine learning classifier and frequency analysis, we simulate two failure states caused by bearing vibrations. Implementing KNN facilitates efficient monitoring, monitoring, and fault-finding for wind turbines. It is possible to reduce downtime, anticipate breakdowns, and import offshore aspects through these technologies.

Design and Implementation of the Sense Egypt Platform for Real-Time Analysis of IoT Data Streams

Nowadays, we experience an abundance of Internet of Things middleware solutions that make the sensors and the actuators are able to connect to the Internet. These solutions, referred to as platforms to gain a widespread adoption, have to meet the expectations of different players in the IoT ecosystem, including devices [1]. Low cost devices are easily able to connect wirelessly to the Internet, from handhelds to coffee machines, also known as Internet of Things (IoT). This research describes the methodology and the development process of creating an IoT platform. This paper also presents the architecture and implementation for the IoT platform. The goal of this research is to develop an analytics engine which can gather sensor data from different devices and provide the ability to gain meaningful information from IoT data and act on it using machine learning algorithms. The proposed system is introducing the use of a messaging system to improve the overall system performance as well as provide easy scalability.

Novel Architecture of OneM2M-Based Convergence Platform for Mixed Reality and IoT

There have been numerous works proposed to merge augmented reality/mixed reality(AR/MR)and Internet of Things(IoT)in various ways.However,they have focused on their specific target applications and have limitations on interoperability or reusability when utilizing them to different domains or adding other devices to the system.This paper proposes a novel architecture of a convergence platform for AR/MR and IoT systems and services.The proposed architecture adopts the oneM2M IoT standard as the basic framework that converges AR/MR and IoT systems and enables the development of application services used in general-purpose environments without being subordinate to specific systems,domains,and device manufacturers.We implement the proposed architecture utilizing the open-source oneM2M-based IoT server and device platforms released by the open alliance for IoT standards(OCEAN)and Microsoft HoloLens as an MR device platform.We also suggest and demonstrate the practical use cases and discuss the advantages of the proposed architecture.

Smart industrial IoT empowered crowd sensing for safety monitoring in coal mine

The crowd sensing technology can realize the sensing and computing of people,machines,and environment in smart industrial IoT-based coal mine,which provides a solution for safety monitoring through distributed intelligence optimization.However,due to the difficulty of neural network training to achieve global optimality and the fact that traditional LSTM methods do not consider the relationship between adjacent machines,the accuracy of human body position prediction and pressure value prediction is not high.To solve these problems,this paper proposes a smart industrial IoT empowered crowd sensing for safety monitoring in coal mine.First,we propose a Particle Swarm Optimization-Elman Neural Network(PE)algorithm for the mobile human position prediction.Second,we propose an ADI-LSTM neural network prediction algorithm for pressure values of machines supports in underground mines.Among them,our proposed PE algorithm has the lowest average cumulative prediction error,and the trajectory fit rate is improved by 24.1%,13.9%and 8.7%compared with Kalman filtering,Elman and Kalman plus Elman algorithms,respectively.Meanwhile,compared with single-input ARIMA,RNN,LSTM,and GRU,the RMSE values of our proposed ADI-LSTM are reduced by 36.6%,52%,32%,and 13.7%,respectively;and the MAPE values are reduced by 0.0003%,0.9482%,1.1844%,and 0.3620%,respectively.

A Low-Cost,Real-Time Rooftop IoT-Based Photovoltaic(PV)System for Energy Management and Home Automation

This work discusses the importance of monitoring and energy management of green energy resources in order to minimize the negative impacts of electricity generation by regular power plants.The paper introduces a highly efficient,low-cost rooftop photovoltaics(PV)solar panel system which can provide monitoring,controlling and automation.The proposed system is based on Internet of Things(IoT)and can be used to control different utilities in any premises automatically or set by the user-defined priority list,as compared to the existing IoT-based PV systems which can only perform monitoring and maintenance of the PV panels or only certain parameters,i.e.,temperature,dust,etc.This is a new step in improving the efficiency of IoT-based PV system where the facility loads are automated by the IoT network.The proposed system can also provide a constant feedback about different parameters,i.e.,voltage,dust,sun irradiance and humidity,etc.,via low-cost open-source platforms for telemonitoring and controlling purposes.The simulation results showthat the proposed system provides a high efficiency to energize the utilities and utilize the available energy as compared to the manual control.