International Transactions in Artificial Intelligence

Anomaly detection using Machine Learning for temperature/ humidity/ leak detection IoT

Harsh Yadav — Wed, 03 Apr 2024 00:00:00 +0000

Anomaly detection plays a pivotal role in ensuring the integrity, reliability, and security of IoT devices, particularly in critical applications such as temperature, humidity, and leak detection systems. This research paper investigates the application of machine learning techniques for anomaly detection in IoT devices deployed for monitoring environmental conditions. We explore the challenges associated with traditional threshold-based methods and propose a data-driven approach leveraging machine learning algorithms for more accurate and adaptive anomaly detection. The study involves collecting real-world sensor data from temperature, humidity, and leak detection IoT devices and developing supervised and unsupervised machine learning models to identify abnormal patterns and anomalies. Various algorithms such as Isolation Forest, One-Class SVM, and Autoencoders are evaluated for their effectiveness in detecting anomalies in sensor data streams. Experimental results demonstrate the superiority of machine learning-based approaches over traditional methods, with improved accuracy, sensitivity, and robustness in detecting anomalous events. The findings of this research contribute to advancing anomaly detection techniques in IoT devices and have significant implications for enhancing the reliability and efficiency of environmental monitoring systems in diverse domains, including smart buildings, industrial facilities, and agriculture.

IoT Security: Issues, Challenges, and Solutions

Prof. Dravid Sood — Fri, 07 Jun 2024 00:00:00 +0000

The rapid proliferation of IoT devices has introduced significant security challenges. This paper reviews the major security issues in IoT ecosystems, including authentication, data privacy, and vulnerability management. It discusses current solutions and proposes strategies to enhance IoT security, emphasizing the need for robust encryption, secure communication protocols, and effective access control mechanisms. The study also explores emerging technologies such as blockchain and AI for IoT security enhancement.

Energy-Efficient Routing Protocols for IoT Networks

Prof. Kounj Harris — Thu, 06 Jun 2024 00:00:00 +0000

Energy efficiency is critical for prolonging the operational lifespan of IoT devices, especially those deployed in large-scale networks. This paper reviews state-of-the-art routing protocols designed specifically for IoT environments to optimize energy consumption. It evaluates protocols based on their ability to minimize communication overhead, reduce packet loss, and prolong battery life. The study discusses the performance metrics used to assess these protocols and proposes directions for future research in energy-efficient routing for IoT networks.

IoT in Healthcare: Opportunities and Challenges

Prof. Pankaj Singh — Fri, 07 Jun 2024 00:00:00 +0000

IoT applications in healthcare promise transformative benefits, from remote patient monitoring to personalized medicine. This paper examines the opportunities and challenges of integrating IoT into healthcare systems. It highlights successful implementations of IoT devices for monitoring chronic conditions and real-time health data analytics. The study also addresses concerns related to data privacy, regulatory compliance, and interoperability standards in IoT-driven healthcare solutions.