AI Road heating optimizer
In collaboration with: Hokkaido Gas
The AI road heating solution uses deep learning and image recognition to recognize various snow conditions.
With better control over the heat source, implementation of this solution can save a significant amount of energy in areas with snowfall.
What is road heating
Heating devices are installed beneath the surface of parking lots, roads and more. The heat sources help to control the amount of snow on the surface, preventing accidents, while eliminating the need for costly snow plows.
Conventional snow sensor control
Maintenance costs often increase due to wasteful operation of heat sources
These systems are installed outdoors to detect surface moisture. (Such systems can not directly observe snowfall on the surface)
As a result, the systems must run the heat sources longer to ensure adequate snow removal, and can not distinguish between rain and snow.
Flow
Thanks to constant data accumulation stored on the cloud, the AI Road Heating Optimizer is able to achieve granular control over road heating, according to the current snowfall conditions and accumulated snowfall on the surface.
Step.1
Step.2
Step.3
The operation status can be confirmed and changed via the internet.
Controller with built-in camera microcontroller
- Raspberry Pi 3 Model B+ :
Accumulation of snowfall is determined by the deep layer - Raspberry Pi Camera Module :
Takes images of the road - LTE Modem :
Monitors the state of the device through an Internet connection
Image recognition AI
Recognizes the snowfall conditions and outputs a signal to operate the boiler at the appropriate time
Original image
Result Snow Not snow
Experiment
The operational time for a boiler (= Fuel cost) used to heat a hospital parking lot in Sapporo City was reduced by 29.0%.
* Reduced energy consumption by up to 85.7% by location
Other applications
snow removal
control
Panel Maintenance