1. A Novel Approach to Rainfall Monitoring
Singapore, 19 January 2022 – Hydroinformatics Institute (H2i) will tap StarHub’s ubiquitous network of mobile base stations as “opportunistic” rainfall sensors, creating a cost-effective rainfall monitoring system in a PUB pilot expected to be launched in the second quarter of the year.
The two companies will mine data on the impact rain has on mobile signal strength to provide PUB with an additional source of rainfall intensity, allowing the national water agency to better anticipate and prepare for heavy rain across the island. This is the first time such a system is being trialled in Singapore, following similar successful implementations in the Netherlands and Germany.
2. Overcoming the Limits of Traditional Rain Gauges
Accurate rainfall readings are critical for water resource management, early flood warnings, and weather predictions.
- The Challenge: Traditional rain gauges are often spaced too far apart to collect high-resolution data. In the tropics, where rainfall varies greatly over space and time, quantifying and forecasting rain can be challenging.
- The Solution: Microwave backhaul links—the wireless connections between mobile base stations—provide an efficient and cost-effective way to plug these information gaps.
- Network Advantage: "The large network of base stations outnumber existing rain gauges, cover a much wider area than weather radar networks, and collect data around the clock," explains the project’s principal investigator Dr. Keem Munsung, a radar specialist with H2i.
3. How Signal Attenuation Data Works
StarHub continuously analyzes micro-changes in signal strength as part of its daily network operations to maintain network quality across thousands of mobile base stations.
- Data Processing: When processed by H2i’s data scientists and rainfall models, these signal variations map rainfall intensity across the island.
- Data Integration: Correlating this data with physical rain gauges, radar, and satellite inputs enables standard rainfall intensity measurements to translate into accurate flood management solutions.
- Privacy & Efficiency: The system requires no new infrastructure or additional capital investment—it simply applies machine learning to existing signal attenuation data. The data relates strictly to signal strength and contains no personal or customer information.
4. Award-Winning Innovation and Pilot Program
The project won the "Cost-effective Rainfall Monitoring" category in the PUB Global Innovation Challenge, selected from 57 applicants across four challenges for its potential to drive operational excellence and address Singapore's future water needs.
- Pilot Execution: The H2i-StarHub team has been commissioned for a Proof-of-Concept (PoC) in Singapore’s southwestern district.
- Future Scaling: Supported with mentorship and test-bedding opportunities from PUB, a successful pilot could progress to a Proof-of-Value stage, covering broader areas before a full national roll-out.
5. Shared Commitment to Climate Resilience
As the World Meteorological Organisation recognizes extreme weather events as the "new norm," pairing water technology scale-up H2i with StarHub highlights the role telecommunications infrastructure can play in climate adaptation.
"From implementing energy-saving measures to adopting renewable energy sources for our network infrastructure, StarHub has been proactively addressing climate change," said Chong Siew Loong, Chief Technology Officer, StarHub. "We are delighted to collaborate with H2i to expand the use of our existing signal attenuation data for an important and meaningful purpose, helping Singapore become more green, sustainable, and resilient."
6. Conclusion & Key Takeaways
Conclusion
By transforming telecommunication infrastructure into a high-density environmental sensing network, H2i and StarHub offer a scalable model for modern urban water management. Without requiring costly hardware deployments, this data-driven partnership unlocks smarter flood forecasting and enhances Singapore's climate resilience—turning everyday mobile network noise into actionable meteorological insight.
Key Takeaways
- Leverages Existing Infrastructure: Converts StarHub’s thousands of mobile base station links into "opportunistic" rain gauges without new hardware costs.
- Fills Data Gaps: Complements traditional weather radars and rain gauges with hyper-local, high-resolution signal data suited for tropical rainfall patterns.
- Privacy-First Data Mining: Uses machine learning on network signal strength data alone—strictly zero personal or customer data involved.
- Phased Rollout: Begins with a Proof-of-Concept (PoC) in southwestern Singapore under the PUB Global Innovation Challenge before scaling nationally.
