Weathering the storm with RFID-IoT and AI, in enhancing student safety

In Malaysia, persistent heavy rainfall poses significant challenges for commuters, including students and employees.

Recent severe floods and monsoon rains have emphasised the urgent need for technological solutions to ensure student safety and the smooth conduct of critical national examinations like the Sijil Pelajaran Malaysia (SPM) and Sijil Tinggi Pelajaran Malaysia (STPM). Despite 395,870 candidates sitting for the SPM 2023 examinations, potential issues, particularly flooding, could hinder students from reaching exam centres.

However, integrating radio-frequency identification (RFID) and Internet of Things (IoT) with artificial intelligence (AI) offers a promising solution, especially in flood-prone states such as Kelantan, Terengganu, and Pahang.

Here are innovative solutions that combine RFID and IoT with AI to create a dynamic system capable of adapting to changing weather conditions:

Flood monitoring infrastructure
Deploying RFID-enabled sensors in flood-prone areas and rivers provides real-time water level data. Integrated with IoT devices, these sensors transmit information to a centralised system, establishing a reliable flood monitoring infrastructure for timely risk assessments.

Automated decision-making
Real-time flood data and predictive analytics support an AI-driven automated decision-making system. This system evaluates the safety of conducting exams or sending students to schools based on current flood risk assessments, ensuring student safety and minimising disruptions to educational activities during adverse weather conditions.

Student safety measures
RFID-enabled student ID cards track students’ movements during their commute, integrating RFID data with AI algorithms to identify the safest routes based on current flood risk assessments. This enhances student safety and optimises transportation logistics during challenging weather conditions.

Online learning platforms
Robust online learning platforms address disruptions caused by physical attendance challenges. AI-powered adaptive learning systems create personalised instructional content, ensuring continuous learning tailored to each student’s needs and preserving academic continuity during erratic weather disturbances.

Flexible exam scheduling
Implementing a dynamic test scheduling system driven by AI allows for adjustments to evolving conditions. Contingency plans for severe weather delays should enable smooth transitions to online assessments or test postponements, ensuring educational resilience in the face of new challenges.

Emergency response planning
Incorporating AI algorithms into emergency response plans enhances authorities’ ability to make prompt and efficient judgments during emergencies. This improves community readiness and response systems, promoting student and community safety.

Continuous improvement
The success of the integrated system relies on continuous improvement. Regular updates, feedback incorporation, and adaptation to emerging technologies ensure the effectiveness of the RFID-IoT and AI solution in handling unforeseen challenges, creating a more adaptive and resilient education system.

The combination of RFID-IoT and AI offers a comprehensive solution to Malaysia’s monsoon rain and flood concerns. Proactively embracing technology ensures student safety, preserves instructional continuity, and dynamically responds to changing weather circumstances.

This holistic approach reduces risks and lays the groundwork for a robust and adaptable education system capable of enduring the unpredictability of the Malaysian monsoon.

Professor Ts Dr Manjit Singh Sidhu is a Professor at the College of Computing and Informatics, Universiti Tenaga Nasional, Fellow of the British Computer Society, Chartered IT Professional, Fellow of the Malaysian Scientific Association, Senior with the Institute of Electrical and Electronics Engineers, and a professional technologist with the Malaysia Board of Technologists.