Journal of Instrumentation Technology & Innovations Review Article

IoT-Based Smart Public Sanitation Monitoring System with Real-Time Air Quality Analysis

  1. Shimpi Harshada Shashikant Department of Artificial Intelligence and Data Science, Jawahar Education Society’s Institute of Technology, Management and Research, Nashik
  2. Kharde Ekata Vinod Department of Artificial Intelligence and Data Science, Jawahar Education Society’s Institute of Technology, Management and Research, Nashik
  3. Gambhir Shruti Hemant Department of Artificial Intelligence and Data Science, Jawahar Education Society’s Institute of Technology, Management and Research, Nashik
  4. Deore Tejaswini Prakash Department of Artificial Intelligence and Data Science, Jawahar Education Society’s Institute of Technology, Management and Research, Nashik
  5. Swati Pandurang Baviskar Department of Artificial Intelligence and Data Science, Jawahar Education Society’s Institute of Technology, Management and Research, Nashik

Abstract

Maintaining hygiene in public sanitation facilities remains a critical challenge in urban environments due to inefficient monitoring and delayed maintenance responses. This paper presents an IoT-enabled smart toilet monitoring system designed to assess and manage restroom cleanliness in real time using environmental sensing and automated decision-making. The proposed system integrates multiple gas sensors (MQ135, MQ8, MQ4) and temperature sensors with an Arduino Uno to continuously monitor air quality parameters such as ammonia, methane, hydrogen levels, and ambient conditions. Sensor data is transmitted to a web- based platform via a client-server architecture, where it is processed using predefined threshold-based algorithms to classify toilet conditions as clean or unclean. The system incorporates RFID-based staff tracking to ensure accountability in maintenance operations. A centralized dashboard provides real-time updates, alerts, and historical logs for municipal authorities, enabling data-driven decision-making and timely intervention. The proposed model enhances transparency, reduces manual inspection efforts, and improves response efficiency in sanitation management. Experimental observations demonstrate the system’s capability to accurately detect hygiene levels and trigger alerts under deteriorating conditions. This approach contributes to smart city initiatives by promoting automated, scalable, and efficient public sanitation monitoring. This system supports sustainable urban development through improved hygiene standards, resource optimization, and reliable public sanitation services.

Keywords

References (13)

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