Objective
Lynxight's mission is to eradicate the problem of drowning, using advanced computer vision and deep learning technologies. Drowning is the second-leading cause of injury death for children under 14, responsible for 6,000 annual fatalities and 650 severe non-fatal injuries daily – all in the EU. With the LYNXIGHT project, Lynxight is developing a swimmer safety management and analytics platform, to be deployed initially in pools and subsequently in additional aquatic venues. Our system detects early signs of water distress, unusual swimmer behavior and a variety of pool analytics to enable proactive life-guarding and optimize operational resources. We fuse multiple pool video sources to create a live 360 degree visual coverage, applying computer vision with deep learning algorithms to uncover safety incidents and swimmer patterns that would otherwise go unnoticed. Lynxight provides facility management with unprecedented visibility and real-time insights that increase swimmer safety, save time and costs and boost the experience for both swimmers and management. Lynxight's system is designed to be very low cost and easy to install and operate, so it can become a widespread and common system in any type of facility. In the same way that technology has advanced other classically “non-technological” industries such as construction and agriculture, we want to improve personal safety in aquatic venues. With a pilot study already underway in Israel and first paying customers, there are strong signs that adoption of this technology, by public pools at start, will be rapid. By 2021 our projections show over 1000 installed systems with over €5M in revenues. Following public pools, we intend to improve the technology so it can cope with additional aquatic venues with more challenging conditions (e.g. beaches and rivers, where the water more volatile and less transparent).
Fields of science
- natural sciencescomputer and information sciencessoftware
- engineering and technologyelectrical engineering, electronic engineering, information engineeringelectronic engineeringsensorsoptical sensors
- natural sciencescomputer and information sciencesartificial intelligencecomputer vision
- agricultural sciencesagriculture, forestry, and fisheriesagriculture
- natural sciencescomputer and information sciencesartificial intelligencemachine learningdeep learning
Programme(s)
Funding Scheme
SME-1 - SME instrument phase 1Coordinator
3200004 HAIFA
Israel
The organization defined itself as SME (small and medium-sized enterprise) at the time the Grant Agreement was signed.