With a growing trend of automation and production volume, the industrial settings safety of workers is gaining importance. Due to high costs, limited scalability, and slow response, traditional environmental monitoring methods (e.g., manual inspection or hardware-based sensor networks) are not acceptable to much of the world’s industrial workforce, especially in small and medium-sized enterprises. This paper presents the design, development, and empirical testing of a Digital Monitoring Framework for Safe Workplaces. This framework is an IoT-centric design that substitutes physical sensing equipment with sensor data generated by algorithms. The system is capable of continuously compiling the data of ambient temperature, an Environmental Safety Index (ESI) which refers to air quality and hazard condition and the seismic activity intensity. Each output is analysed upon generation with an adjustable set of safety thresholds based on machine users’ occupational health standards. The system activates a multi-level alert system when a violation is detected. This ensures that the violation is categorized as Warning, Critical or Emergency which is displayed on the graphical map of monitoring.