BACKGROUND

Oil and chemical spills (usually involving volatile substances such as hydrocarbons and toxins) are high-risk incidents particularly in busy port waters such as that of Singapore. Spill detection often relies on visual reporting, delayed satellite data, or post-incident water sampling involving multiple organisations [e.g. Maritime & Port Authority of Singapore (MPA), other incident response agencies, and external contractors]. Cloud cover, low light, wave action, and heavy rain impact visibility which cause delays in detection and response times.

SIGNIFICANCE OF PROBLEM

Fast identification is critical — delayed detection of even small spills (<100L) can lead to costly cleanups, port shutdowns, reputational damage, and harm to the ecosystem (e.g. beaches, fish farms, marine life, etc). Responders are challenged with false alarms, poor visibility, and fragmented systems that cannot work in all weather conditions.

POTENTIAL MARKET SIZE

The global oil spill detection and response tech market is valued at $2.5B, growing with increased environmental regulations. The Asia-pacific region is a key market due to high shipping volumes and stricter port-state controls.

EXISTING EFFORTS

Use of satellite imagery, CCTV, and aerial patrols; some pilot programmes for drones. However, many these systems are not real-time, weather-resilient, or scalable.

Gaps in existing efforts:

• Lacks real-time recognition of oil spill (detection, extent/size and oil type)
• Lacks real-time data collection and transmission (with latency <1 min needed)
• Slow deployment, launch and recovery where required (<10 mins needed)
• Inability to operate in shallow water and with extended range
• Less than 95%+ detection accuracy in low visibility and bad weather
• Not deployable in busy port waters