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An AI-driven solution for enhancing safety at construction sites. Utilises YOLOv8 for object detection to identify overhead hazards like heavy loads and steel pipes. Alerts are triggered if personnel are detected beneath these hazards. Dataset sourced from Taiwan's construction industry.
Optical sensor to detect hazardous gas in corrosive environment. Showcasing my Raspberry Pi project combining electrical engineering and sensor detection.
The Hazard Recognition Challenge allows you to perform a virtual workplace examination. Your goal is to find as many hazards as possible at a work location.
The research mainly aims to identify through classification algorithms if one day, based on its climatic features and concentrations of harmful elements in the air, it turns out to be harmful (or not) to the health of citizens in the Milan metropolis. A second prediction model was adopted to predict daily mean PM2.5 values.
Design, verification and ASIC implementation of a complete RISC-V CPU with: five stages pipeline, forwarding, automatic hazard detection, Branch Target Buffer using LRU replacement policy, absolute value custom instruction.
Design and development of a complete RISC CPU with: five stage pipeline, forwarding, automatic hazard detection, BTB using LRU policy replacement, four-cycle hardware multiplier.