Internet of things

Machine learning

Blockchain Enhanced Distributed Denial of Service Detection in IoT Using Deep Learning and Evolutionary Computation

Researchers from the Chaitanya Bharathi Institute of Technology have proposed a new framework for detecting Distributed Denial of Service (DDoS) threats in Internet of Things (IoT) environments using advanced techniques. The Metaheuristic-Optimized Blockchain Framework for Attack Detection using a Deep Learning Model (MOBCF-ADDLM) method employs blockchain technology to mitigate DDoS

Machine learning

Artificial Intelligence Enhances Agricultural Water Resource Management

Researchers at Islamic University have developed an Artificial Intelligence-based system, AWRM-AI, to optimize agricultural water resource management, reducing waste and ensuring crops receive the precise amount of water needed. This innovative approach leverages IoT sensors to monitor environmental variables and uses AI algorithms to analyze the data and make real-time

Sensors

Blockchain-Based Mobile IoT System with Configurable Sensor Modules Shows Potential for Reliable Data Collection

A team of researchers from Dankook University has developed a novel Multi-Sensor IoT Device (MSID) that combines environmental data collection, cloud connectivity, and blockchain-based storage to ensure reliable data management. This innovative system, known as the Blockchain-Based Mobile IoT System (BMIS), has demonstrated strong potential for use in various applications,

Sensors

Researchers from University of Cagliari Report Details of New Studies and Findings in the Area of Engineering

Researchers affiliated with the University of Cagliari have conducted a new study on engineering, with their findings published in recent research. The study focused on developing a solution for forest fire detection, utilizing LoRa technology, wireless sensor networks, and a feed-forward neural network. The proposed method was validated on a

Sensors

IoT Adoption in Healthcare and Banking: Challenges and Framework for Addressable

Research from Manchester Metropolitan University has revealed the crucial societal and organisational impacts of IoT adoption in healthcare and banking sectors. The study identifies key applications of IoT, its social and organisational drivers, and the challenges of its implementation. The analysis highlights security, privacy, interoperability, and legal compliance as critical

Sensors

Breakthrough in Sensor Research: X-FuseRLSTM Promises Improved IoT Security

Researchers from King Abdulaziz University have made a significant breakthrough in sensor research, presenting a novel algorithm, X-FuseRLSTM, designed to enhance cross-domain intrusion detection in heterogeneous and dynamic IoT systems. The proposed algorithm combines deep encoder and sparse transformer features with a residual LSTM architecture, achieving high accuracy rates on

Sensors

Vulnerable-by-Design IoT Sensor Framework for Cybersecurity in Smart Agriculture

Researchers at Technical University in Romania have unveiled a groundbreaking study that highlights the unique cybersecurity challenges faced by Agricultural Internet of Things (IoT) deployments due to resource constraints and direct impact on food production. The study introduces a vulnerable-by-design, containerized IoT framework simulating both cybersecurity vulnerabilities and sensor health

Machine learning

Novel Multistage Adversarial Attack Defense Framework for DDoS Attack Detection Systems

Investigations at Addis Ababa University have led to the development of a novel Multistage Adversarial Attack Defense (MSAAD) framework to protect online DDoS attack detection systems from adversarial attacks. This breakthrough framework consists of three defense layers, designed to detect and prevent DDoS attacks in IoT systems. The MSAAD framework

Machine learning

Enhancing Privacy in IoT Networks: A Comparative Analysis of Classification and Defense Methods

Researchers at Edge University have made a significant contribution to the field of engineering by detailing new data on the privacy concerns associated with the rapid proliferation of Internet of Things (IoT) devices. According to the study, the increase in network packet traffic due to IoT devices has raised significant

Machine learning

Machine Learning Optimizes Carbon Footprint in IoT Networks

Artificial intelligence and machine learning techniques can significantly reduce the environmental impact of Internet of Things (IoT) networks. Researchers from the Department of Information and Communication Technologies, Universidad Politécnica de Madrid, have developed an optimization framework leveraging machine learning to minimize the carbon footprint associated with IoT multi-hop network deployments.

Machine learning

Artificial Intelligence-Based Monitoring System for Elderly Care: A Study on Human Activity Recognition

Researchers from Mediterranea University of Reggio Calabria have developed an artificial intelligence-based monitoring system to support the care of elderly individuals. The system, which combines Internet of Things (IoT) technologies with machine learning algorithms, is designed to recognize human movements and activities, allowing healthcare staff to assess the motor skills

Machine learning

Advances in Machine Learning-Based Intrusion Detection in IoT Networks Revealed

Research from the Technical University of Denmark (DTU) has uncovered trends and challenges in machine learning-based intrusion detection in Internet of Things (IoT) networks. The study, which analyzed datasets and machine learning techniques used from 2019 to 2024, found that certain datasets, such as BoT-IoT and TON_IoT, combined with