The Internet of Things (IoT) is another useful perspective that brings questions from different disciplines together over the Internet. As more wearable technologies become available on market, teleworking in Wearable Wireless Body Area Networks (WBAN) becoming widespread for Things-related medical applications. This article proposes a solar-powered touch sensor based complete social network (SPWT) and Wi-Fi transmission connects to WBAN. Different focal points can be assigned frame...

Real-time monitoring and analysis of data from various sources have been made possible due to the growth Internet Things (IoT)-enabled embedded systems in military applications. This has allowed improved situational awareness identification potential threats. However, it is essential that communication between these be protected against illegal access intervention maintain their integrity. research study investigates whether or not encrypted make use IoT for purposes. It gives an overview...

Flooding has often been caused by an increase in the volume of water a system, such as lake or river overflowing. On rare occasions, dam will crack, releasing tremendous amount water. As result, some seeps into soil, 'overflowing' area. Rivers are intertwined with banks at station. Aside from lack items and assets, municipal architecture rainwater contains germs wastewater flows dumping grounds toxic leaks, resulting various ailments. The purpose this research is to identify existence beds...

The exponential advancements in recent technologies for surveillance become an important part of life. Though the internet things (IoT) has gained more attention to develop smart infrastructure, it also provides a large attack surface intruders. Therefore, requires identifying attacks as soon possible provide secure environment. In this work, network intrusion detection system, by applying ensemble model (NIDSE) Smart Homes is designed identify home devices. problem classifying considered...

Microplastic pollution in water systems is growing, requiring novel detection and analysis methods. This research presents an Internet of Things (IoT)-driven image identification system using Convolutional Neural Networks (CNNs) to detect quantify microplastics samples. The suggested method more scalable responsive due IoT real-time data capture remote monitoring infrastructure. An innovative CNN architecture for processing allows the accurately identify micro plastics. model trained...

The increasing use of electric vehicles (EVs) highlights the need a designed effectively charging network. This paper presents novel way for EV by establishing smart hub network using dynamic K-means clustering. unpredictable nature patterns makes static clustering systems difficult to maintain up, which leads inefficiency and load at points. failure current vehicle facilities adapt altering in unsatisfactory experiences customers. These issues are exacerbated station mismatches an inability...

This research proposes an efficient approach to improve hospital worker safety on the job by detecting and preventing drowsiness. The system incorporates data from hospital-deployed Internet of Things (IoT) infrastructure using Support Vector Machines (SVM) as its primary predictive modeling tool. Data pertaining ambient factors, work habits, physiological indications employees are collected in real-time IoT infrastructure. To identify patterns linked sleepiness, SVM model is trained...

Security provisioning has become an important issue in wireless multimedia networks because of their crucial task supporting several services. This paper presents Bayesian decision model based reliable route formation internet things (BDMI). The main objective the BDMI approach is to distinguish unreliable sensor nodes and transmit data efficiently. Active passive attack recognition methods identify node nodes. Remaining energy, degree, packet transmission rate parameters observe...

The Internet of Things (IoT)-powered black box for advanced driver behavior analysis and vehicle safety is a revolutionary strategy improving road via the use boxes powered by Things. This project captures realtime data on driving behavior, encompassing characteristics such as speed, acceleration, braking, adherence to lanes seamless integration IoT technologies into vehicle's box. It does this providing in-depth insights drivers' behaviors, which encourages adopting safe practices thanks...

Sustainable urban mobility requires optimizing public transit passenger experiences. This system integrates cloud technologies and the Random Forest algorithm with bus fare ticketing systems to improve efficiency customer pleasure. Cloud provide real-time data processing for price structure route optimization in research. computing lets transportation providers quickly adjust shifting demand, enhancing service dependability responsiveness. The is integrated into procedures estimate demand...

The cloud-based road safety technology introduced in this research improves real-time vehicle behavior monitoring and warns for rash driving. It uses cloud computing to gather interpret data from onboard car sensors other traffic equipment. Powerful machine learning the Random Forest (RF) algorithm analyses intelligently. RF is trained on a varied array of driving metrics detect tendencies. Real-time streams may be processed efficiently scalable cloud, enabling speedy decision-making...

This study uses intelligent headlights to improve car safety and economy. The suggested system Raspberry Pi Convolutional Neural Networks (CNNs) dynamically modify beam patterns real-time ambient circumstances context. is a flexible computer platform, CNNs automatically analyze sensor video data headlight patterns. A trained CNN model recognizes impending vehicles, pedestrians, road conditions. By analyzing this information, the optimize pattern maximize visibility minimize user glare....

The proposed system integrates face recognition and Internet of Things (IoT) technology to revolutionize the hospitality industry. It uses OpenCV, a widely recognized computer vision library, deliver smooth, contactless guest services rigorous identification verification. This paper proposes novel method improve visitor experiences by removing check-in allowing personalized services. IoT -enabled presented in this streamlines experiences. Facial biometrics eliminates need for identity...

Frequent and unregulated use of antimicrobials (AM) in livestock requires public health attention as a likely selection pressure for resistant bacteria. Studies among small-holders, who own large percentage the world's livestock, are vital understanding how practices involving AM might influence resistance. We present cultural-ecological mixed-methods analysis to explore sectors veterinary care, loosely regulated use, human exposure AMs through meat milk consumption across three rural...

Abstract Antibiotic use and bacterial transmission are responsible for the emergence, spread persistence of antimicrobial-resistant (AR) bacteria, but their relative contribution likely differs across varying socio-economic, cultural, ecological contexts. To better understand this interaction in a multi-cultural resource-limited context, we examine distribution enteric bacteria from three ethnic groups Tanzania. Household-level data ( n = 425) was collected isolated people, livestock, dogs,...

Views Icon Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Twitter Facebook Reddit LinkedIn Tools Reprints and Permissions Cite Search Site Citation M. Senthil Kumar, H. Azath, A. K. Velmurugan, Padmanaban, Murugan Subbiah; Prediction of Alzheimer's disease using hybrid machine learning technique. AIP Conference Proceedings 30 January 2023; 2523 (1): 020091. https://doi.org/10.1063/5.0110283 Download citation file: Ris (Zotero) Reference Manager EasyBib...

Views Icon Article contents Figures & tables Video Audio Supplementary Data Peer Review Share Twitter Facebook Reddit LinkedIn Tools Reprints and Permissions Cite Search Site Citation A. K. Velmurugan, Padmanaban, M. Senthil Kumar, H. Azath, Murugan Subbiah; Machine learning IoT based framework for analysing heart disease prediction. AIP Conference Proceedings 30 January 2023; 2523 (1): 020038. https://doi.org/10.1063/5.0110179 Download citation file: Ris (Zotero) Reference Manager EasyBib...

Wireless Sensor Networks (WSNs) are essential for IoT-enabled crisis management and executive response. This paper explores WSNs' function in catastrophe situations proposes new ways to improve emergency response operations. The article begins with a discussion of disaster scenarios the necessity real-time data collecting, monitoring, analysis. WSNs suitable such applications due their dense dispersed sensing, tolerance hostile conditions, low power consumption. research provides unique WSN...

Indian Sign Language (ISL) is the principal mode of communication for most dumb and deaf citizens nationwide. ISL uses signs movements hands, faces, or body postures to transmit needed message emotion. These may be read by those that are unaware ISL. It a fully developed natural language has its lexicon as well syntax. Translation systems essential eliminate barrier between community hard-of-hearing people. To facilitate effective two-way hearing-impaired general population society, proposed...

Traffic jams and drivers looking for parking spaces are caused by the increased urbanization vehicle population. This paper proposes an intelligent guidance system that effectively manages spots using Internet of Things (IoT) Machine learning methods. The uses IoT sensors cameras positioned in lots to track occupancy status specific real-time. acquired data is sent a cloud server analysis processing. Convolutional Neural Network (CNN) algorithm, deep approach, used evaluate camera images...

The stability and dependability of the grid are crucial importance as integration photovoltaic (PV) systems into electricity grids gathers momentum. Because their bidirectional power flow intermittent energy production, PV present a variety issues when it comes to quality (PQ). Effective management limited by fact that conventional monitoring techniques have difficulties in providing real-time insights harmonics, voltage stability, transient disturbances. can only function at peak efficiency...

The protection of user privacy and mitigation threats like spoofing, DoS, jamming, eavesdropping are essential for the Internets Things (IoT) to fulfill its promise bringing improved intelligent services users via integration diverse devices into networks. Machine learning (ML) approaches, including supervised learning, unsupervised Reinforcement Learning (RL), explored as potential solutions securing IoT. This article focuses on use ML in IoT authentications, access controls, secured...

Cyberspace has grown due to the widespread uses of Internets and mobiles apps. Attacks on Internet are more likely be automated last longer. Cyber security techniques make it possible improve measures against cyber-attacks. Because modern fraudsters so sophisticated, traditional no longer effective. Conventional solutions must revised when identifying new evolving threats. Many cyber applications would only using machine learning (ML) methods. Despite this continued improvement, major...

One of the latest techniques for bridging gap between real world and digital one is Internet Things (IoT). Monitoring electrical physical factors made easier by IoT. There are a number issues with existing that used solar-powered building energy monitoring. Traditional monitoring systems sometimes too expensive many customers, requiring complicated installations, gear, specialized software. These could also be unable to give accurate, real-time data on usage, which would restrict their...