Wildlife Detection Network
Independent thesis Basic level (degree of Bachelor), 15 credits / 22,5 HE creditsStudent thesis
Traffic accidents where wild animals are involved represents between 60 and 80 percent of all reported accidents, depending on location in Sweden. In a country like Sweden, with a lot of forest, there is always risk of a collision with a wild animal. Imagine if you, as a road user, had the possibility to receive warnings when the risk of an accident according to statistics is extra high.
Wildlife Detection Network is a wildlife warning system with an information service, which makes the whole concept unique. When an animal is approaching the road, it is registered by sensors, and warning lights along the road are lit to inform drivers of the potential danger. In conclusion, this is a direct warning to all drivers on the road where the system is placed.
When an animal is registered by the sensors, information containing time, date, weather circumstances and coordinates are sent to a database. The database stores information about the animal activity in the area, and will read out activity patterns for the animals. For example, the risk for a collision might be higher between 6.00 and 8.00 AM when the temperature is about ten degrees.
When you approach the measured area in your car, you will receive a warning in you smartphone or GPS-unit. The warning tells you that the risk of encountering a wild animal along the road is high during the current circumstances. The associated service works as a complement for those that further wants to reduce the risk of a wildlife accident.
We are well aware of that wildlife accidents are a very complex and in particular intractable problem. The two of us behind Wildlife Detection Network are proud of our concept and we are hopeful that our system will contribute to a decrease in wildlife accidents in the future.
Place, publisher, year, edition, pages
2012. , 65 p.
viltolyckor, viltvarning, WDNet, sensorer, rörelsemönster, vilt, djur
Mechanical Engineering Other Engineering and Technologies not elsewhere specified
IdentifiersURN: urn:nbn:se:hh:diva-17765OAI: oai:DiVA.org:hh-17765DiVA: diva2:529436
Subject / course
2012-05-16, 12:00 (Swedish)