Development of an integrated and multi-sensor IoT device for smart toilets and smart facilities

• Main Author: Tan, Kevin Jan Ming
• Other Authors: Soh Yeng Chai
• Format: Final Year Project
• Language: English
• Published: Nanyang Technological University 2024
• Subjects: Engineering; Internet of Things
• Online Access: https://hdl.handle.net/10356/176610
• Institution: Nanyang Technological University

This research paper outlines the process of designing and developing an IoT smart module capable of monitoring the toilets in train stations. This plug-and-play innovation consists of several sensors (people counter, ammonium detection, bin occupancy, temperature & humidity, and air quality) which are linked to an Arduino UNO board and a LoRa transceiver. This initiative aims to improve efficiency and reduce costs for SBS Transit by adopting a clean-by-demand model, where the toilets are cleaned based on status. Additionally, it addresses the manpower constraints faced in Singapore by enabling remote management of multiple toilets for cleaning personnel. The solution was effectively constructed by soldering wires together to establish connections between the various components. The LoRaWAN gateway will then receive the data from the Arduino board and send it to the Node-RED dashboard for visualisation purposes. Selecting LoRa as the preferred network connectivity for this project is due to its long-range communication and wall penetration capabilities, which makes it extremely compatible with the project scope. The connection between the LoRaWAN gateway and the Node-RED dashboard is made possible by the EMQX message broker, which operates on a publish-subscribe model. This prototype has the potential to pave the way for widespread adoption across Singapore’s land transportation network, with SBS Transit managing close to 50 train stations across the country. The project could explore the possibilities of implementing a mobile application for notifying cleaners or creating a database system for trend analysis and reporting. Leveraging big data analytics could further optimise resource allocation and sustainably digitalise operations. Overall, this research project represents a significant step forward in helping SBS Transit improve productivity and enhance commuters' experience.