International Journal of Human Computer Interaction and Data Mining

A Systematic Review on IoT and AI Powered Smart Parking Technologies for Urban Environments

2026-06-01T11:17:00+00:00

The number of cars in cities has expanded dramatically, making it more difficult to manage parking effectively and contributing to traffic jams, fuel waste, and environmental damage. Up until now, traditional parking systems—which are either sensor-based or manually operated—have had trouble adapting to changing urban mobility and dynamic traffic circumstances. Unprecedented developments in computer vision and the Internet of Things (loT) have created opportunities for intelligent, reasonably priced, and highly scalable parking solutions that can instantly monitor, assess, and manage spots. This paper's goal is to review the literature on state-of-the-art research in smart parking systems using computer vision and loT technology, highlighting technological developments that have improved functionality and performance as well as implementation issues and future development opportunities. In particular, this research employs a systematic review approach to investigate how the development of parking management techniques for smart cities is being driven by current models incorporated with lightweight YOLO architecture on edge computing and adaptive control algorithm technology. Limitations resulting from system scalability, data security, and environmental conditions are also examined, along with recommendations for potential future enhancements using sensor fusion methods and Al-driven analytics.

Ethics of AI in Decision-Making: Striking a Balance Between Progress and Responsibility

2026-05-03T13:29:14+00:00

Artificial Intelligence (AI) is transforming various sectors, from healthcare and finance to the criminal justice system, by enabling faster and more data-driven decision-making. However, these advancements raise critical ethical concerns. Can we trust AI to make fair and accountable decisions that impact human lives, rights, and futures? This paper examines the ethical challenges of AI-driven decision-making, focusing on issues such as bias, transparency, accountability, privacy, and autonomy. It explores how AI systems can reinforce societal inequalities, operate with limited human oversight, and lack clear explanations for their decisions. Additionally, the paper discusses strategies for developing ethical, responsible, and fair AI systems that align with human values and societal expectations. Ensuring AI serves the greater good requires a balanced approach that integrates fairness, explainability, and accountability into its design and deployment.

DOI: https://doi.org/10.24321/3117.4841.202501

Design of Integrated Health Monitoring System on IoT Based Framework

2026-02-07T07:21:16+00:00

With the advent of industrialization, health ailments have become major cause of concern owning to inactive and fast lifestyle, polluted environments, and detrimental eating habits. However, IoT has become a boon for the Health Sector and humanity on account of its countless benefits, rendering improved quality of service and patient-centric care. The Integrated Health Monitoring System is presented in this paper, i.e., sensors within a new IoT-based framework, the IHMS, which integrates wearable technology with secure cloud analytics addressing the current challenges and improving the quality of service. This paper further investigates significant IoT applications in healthcare, remote patient monitoring, intelligent medical devices and hospital resource optimization, and gives a detailed analysis of the IHMS model, the structure of model and the capabilities to change the standards of current healthcare systems.