Journal of Advanced Research in Computer Graphics and Multimedia Technology

Behaviour Prediction of Shrimp using trajectory analysis and their validation with deployed IoT Sensor

2025-10-03T09:59:14+00:00

This study presents a comprehensive end-to-end pipeline for real-time monitoring and behaviour prediction of shrimp locomotion in variable environmental conditions, integrating state-of-the-art deep learning, computer vision, and signal processing methodologies. The framework combines an enhanced YOLOv8 detection system with Deep SORT tracking algorithms and implements a sophisticated hybrid trajectory denoising approach utilising Savitzky-Golay filtering, cubic spline interpolation, and Gaussian smoothing. Applied to a custom-annotated dataset of 789 underwater shrimp images, the detection model achieved 0.74 precision, 0.856 recall, and 0.794 mAP@0.5. Advanced trajectory analysis techniques enabled 3D visualisation and directional behaviour quantification under four distinct environmental regimes combining pH variations (5.4.6.8) and temperature conditions (33°C, 35°C). A comprehensive comparative analysis with recent advances in underwater object detection, particularly YOLOv8-CPG architectures incorporating Compact Inverted Blocks (CIB), Partial Self-Attention (PSA), and Gold-YOLO feature fusion mechanisms, demonstrates potential performance improvements of 1-3% mAP through architectural optimisation. The methodology's integration with precision aquaculture monitoring systems, IoT sensor networks, and real-time behavioural alerting mechanisms positions it as a critical tool for sustainable aquaculture management, environmental stress detection, and automated welfare assessment in intensive farming operations.

Smart Automated Warehouse System for E-Commerce Order Packaging Model

2025-10-03T10:56:15+00:00

The rapid growth of e-commerce has greatly increased the demand for rapid, accurate and contact-free order supply. To meet these developed expectations, the automated warehouse system has emerged as a practical solution to increase operational efficiency. The project introduces a smart, automated warehouse system that basically integrates real-time web communication with physical automation to customise the packaging process.

Utilization of IoTs and AI to Modernize Academic Libraries

2025-10-03T10:09:58+00:00

Academic libraries have long been considered the cornerstone of higher education institutions, supporting learning, teaching, and research. With the onset of digital transformation and Industry 4.0 technologies, libraries are under increasing pressure to reinvent themselves to remain relevant to the modern academic community. Two of the most powerful technologies influencing this change are the Internet of Things (IoT) and Artificial Intelligence (AI). The integration of IoT devices with AI systems has created opportunities to design “smart libraries” that provide efficient resource management, enhanced security, personalised services, data-driven decision-making, and enriched user experiences. This paper provides an in-depth exploration of how IoT and AI can be applied to modernising academic libraries while also addressing challenges, case studies, and future prospects.