When traffic volumes in a city are monitored, data accumulates. Making sure the the data is up-to-date, accurate and sufficiently diverse, is a demanding task. The City of Tampere solved data quality and cost challenges with a machine vision solution based on Wapice’s IoT-TICKET® -platform and artificial intelligence.
Tampere, a fast-growing city, faced a challenge in traffic planning. Pedestrian traffic volumes were measured with less than ten fixed traffic counters, and the rest of the required calculations were largely done by human resources, using sample counts.
“We had tested AI-based solutions before, but they had image recognition built in the camera itself and implementing the solution would have required the purchase and installation of new special cameras. In Wapice’s solution, image recognition is performed centrally using so-called edge computing, allowing us to make use of existing cameras and communication infrastructure. So basically we would buy an analytics application and server capacity, not cameras. For this reason, Wapice’s solution turned out to be considerably more affordable than fixed counters and previous image recognition solutions,” says Jarno Hietanen, traffic planning engineer in the City of Tampere.
- Wapice Oy, Jari Kuusisto, Product Manager, IoT for Smart Cities, Tel. +358 44 553 3512, email@example.com
- Wapice Oy, Mickey Shroff, Head of AI, Analytics and Automation Solutions at Wapice, Tel. +358 50 302 7187 firstname.lastname@example.org
- Tampere City, Jarno Hietanen, Traffic planning engineer.
Image of the article: ©Visit Tampere / Laura Vanzo