Nowadays, waste management faces the challenge of providing effective and efficient solutions for waste collection, disposal, and recycling while respecting health and environmental standards. This challenge also includes the lack of understanding of the diverse factors that influence the various stages of waste management, inefficient route planning, insufficient resources, etc. Faster collection, management, and processing of waste are possible with smart containers and IoT technologies allowing waste real-time data provision. Thus, this research proposes a waste management system based on generic and comprehensive generic context ontology and smart containers. The context ontology is conceived to solve the limits and the insufficiencies of waste management by covering all the waste facets for all the stakeholders, optimizing, analyzing, and reusing the waste data and conditions. For given smart container and waste management context, we need to have a global view of the relevant contextual data according to a unified model such as the waste environment data, the waste activity context, the waste computing context, the user context, the collaboration context, etc. One significant advantage of our system is that it provides a unified model for waste management contextual data that could be reused for other waste management systems covering all the properties of this domain. The proposed solution implements an intelligent and adaptive IoT system for waste management according to different waste contexts, waste objectives, and waste activities. The proposed system has been successfully tested under different scenarios in Jeddah City Municipality.

This research presents an innovative Internet of Things (IoT) and artificial intelligence (AI) platform designed to provide holistic assistance and foster autonomy for visually impaired individuals within the university environment. Its main novelty is real-time sensory augmentation and spatial awareness, integrating ultrasonic, LiDAR, and RFID sensors for robust 360° obstacle detection, environmental perception, and precise indoor localization. A novel, optimized Dijkstra algorithm calculates optimal routes; speech and intent recognition enable intuitive voice control. The wearable smart glasses are complemented by a platform providing essential educational functionalities, including lesson reminders, timetables, and emergency assistance. Based on gamified principles of exploration and challenge, the platform includes immersive technology settings, intelligent image recognition, auditory conversion, haptic feedback, and rapid contextual awareness, delivering a sophisticated, effective navigational experience. Exhaustive technical evaluation reveals that a more autonomous and fulfilling university experience is made possible by notable improvements in navigation performance, object detection accuracy, and technical capabilities for social interaction features, according to a thorough technical audit.