Citation :

M.Ragu, Dr.S.David Blessley, 2026. "Underground Drainage Cleaning Accident Prevention" ESP International Journal of Advancements in Science & Technology (ESP-IJAST)  Volume 4, Issue 1: 53-59.

Abstract :

Manual cleaning of underground drainage systems is grossly inadequate and one of the world's most dangerous occupations that expose sewage workers to toxic gases, oxygen deficiency, structural collapse and fatal accidents. The deaths are mostly due to inhalation of toxic gases such as methane (CH₄), hydrogen sulfide (H₂S), ammonia (NH₃) and carbon monoxide (CO) that can be found in the mines. While many different aspects of emergency response systems is more efficient than in the past, they are not fit for purpose within an underground sewage treatment works. This project work involves smart accident prevention and emergency response mechanism for under ground drainage cleaning by developing an intelligent AI protocol based monitoring system with automated lift control device along emergency gas suction mechanism. Composed of advanced gas and environmental sensors, the system continuously monitors toxic gas with detecting oxygen concentration, temperature and workers activity. With the help of an AI module, these systems can identify abnormal real-time conditions (floods, mudslides, etc.), analyze data to predict adverse conditions and adopt preventive measures. For example, when the system identifies the presence of hazardous gases in large quantities, it uses a high-capacity gas suction mechanism to vigorously extract toxic gases present within and create an oxygen-rich environment. Simultaneously, an automatic lift control system kicks into gear to transport the worker outside of the underground space for safety reasons. It works as a complement with GSM/IoT communication modules to notify supervisors. Our proposed solution reduces degeneracy on manual supervision, keeps workers safe at all times, provides high speed of emergency response and lastly reduces deaths in sewage working. A smart, holistic life-saving underground drainage formulation that combining the intelligence technology and machine hydraulics to allow one hide from such disasters with AI sensor network + mechanical lift-up mechanism.

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Keywords :

AI-Based Safety, Gas Detection, Emergency Evacuation, IoT Monitoring.