Internet measurement in Thailand

This episode of PING features two members of the Thai academic and research community and was recorded last year at IETF 122 in Bangkok. With a population of more than 70 million, Thailand has around 80 publicly funded universities and a further 70 or more private institutions, and undertakes substantial research in telecommunications and computing. A leading example is the Asian Institute of Technology (AIT), which has run the AINTEC conference across the Asia Pacific. Both of our guests on this episode are associated with AINTEC. First, we hear from Sukumal Kitisin of Kasetsart University, a state-funded institution. She has been working on an Internet measurement programme for the Thai Consumer Council (TCC). The project leverages well-known tools such as Ookla Speedtest and OpenSignal to capture end-user experiences of mobile Internet services in Thailand. These measurements support modelling of broadband speeds and service quality, which the TCC can then use to present consumer evidence to the national telecommunications regulator, the National Broadcasting and Telecommunications Commission (NBTC). While we are often accustomed to discussing measurement using Atlas probes and other ‘insider’ approaches, this work represents a consumer-friendly, simple, and defensible method for capturing the lived experience of real-world users. Secondly, we hear from Adisorn Lertsinsrubtavee, Director of the Internet Education and Research Laboratory (InterLab) at AIT. Adisorn describes a decade-long measurement effort known as HAZEMON, which focuses on low-bandwidth Internet of Things (IoT) devices used to measure suspended particulate matter such as smoke and fumes from diesel and charcoal fires, as well as carbon monoxide and carbon dioxide. Thailand sits at the heart of a South East Asian climate system that is heavily affected by forest fires and persistent smog, with serious health implications. PM2.5 particles can penetrate deep into the lungs and cause lasting respiratory and other health problems as they are absorbed into the body. Monitoring these levels enables the project to model pollutant density, identify significant events such as forest fires, and support on-the-ground responses by firefighting teams and health professionals. The measurwement system uses small, low-energy computing platforms with off-the-shelf particulate sensors, integrated with low-bandwidth radio systems and powered by solar or battery sources where mains electricity is unavailable. These units are deployed across forests and urban areas, with data federated back to AIT for analysis.