This product was not featured by Product Hunt yet. It will not be visible on their landing page and won't be ranked (cannot win product of the day regardless of upvotes).
SolarPowered Traffic Monitoring Solution
Counts the number of passing cars and finds their direction
The goal of this project was to develop a solar-powered device that counts the number of vehicles passing in each direction through a specific point on the university campus and periodically upload that data to an online MySQL database for easy access for data analysis. The device can be deployed entirely powered be solar and a battery. Data retention is kept to a minimum and all processing is done on-device.
This was my final-year thesis project for my Computer Engineering degree. The goal was a self-powered, camera-based device to count vehicles by direction at a specific point on a road, without needing to tap into road infrastructure. Runs on a Raspberry Pi 5 4GB (although 2GB should work fine too) with a basic 720p USB webcam. Detection is based on the YOLOv8 Nano, then a Kalman filter + greedy IoU tracker maintains vehicle IDs across frames and classifies direction of travel.
On my test footage it hit 96.6% detection/classification accuracy. It also works at night if there is street lighting.
Powering it is a 100W solar panel + 600Wh lead-acid battery, sized using PVGIS irradiance data, modeled to survive at least 3 winter days worst-case. Measured draw is 5.6W average (power optimization details on the website).
Privacy was a real design constraint. All inference happens on-device, frames only ever exist in RAM, and the only thing that leaves the device is an anonymized, aggregated vehicle count per time period.
No comment highlights available yet. Please check back later!
About SolarPowered Traffic Monitoring Solution on Product Hunt
“Counts the number of passing cars and finds their direction”
SolarPowered Traffic Monitoring Solution was submitted on Product Hunt and earned 2 upvotes and 1 comments, placing #160 on the daily leaderboard. The goal of this project was to develop a solar-powered device that counts the number of vehicles passing in each direction through a specific point on the university campus and periodically upload that data to an online MySQL database for easy access for data analysis. The device can be deployed entirely powered be solar and a battery. Data retention is kept to a minimum and all processing is done on-device.
SolarPowered Traffic Monitoring Solution was featured in Cars (6.3k followers), Artificial Intelligence (479.9k followers) and Tech (633.6k followers) on Product Hunt. Together, these topics include over 297.4k products, making this a competitive space to launch in.
Who hunted SolarPowered Traffic Monitoring Solution?
SolarPowered Traffic Monitoring Solution was hunted by Marios Christoforou. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how SolarPowered Traffic Monitoring Solution stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
Marios Christoforou
This was my final-year thesis project for my Computer Engineering degree. The goal was a self-powered, camera-based device to count vehicles by direction at a specific point on a road, without needing to tap into road infrastructure.
Runs on a Raspberry Pi 5 4GB (although 2GB should work fine too) with a basic 720p USB webcam. Detection is based on the YOLOv8 Nano, then a Kalman filter + greedy IoU tracker maintains vehicle IDs across frames and classifies direction of travel.
On my test footage it hit 96.6% detection/classification accuracy. It also works at night if there is street lighting.
Powering it is a 100W solar panel + 600Wh lead-acid battery, sized using PVGIS irradiance data, modeled to survive at least 3 winter days worst-case. Measured draw is 5.6W average (power optimization details on the website).
Privacy was a real design constraint. All inference happens on-device, frames only ever exist in RAM, and the only thing that leaves the device is an anonymized, aggregated vehicle count per time period.
Full writeup and thesis report on my website.