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The problem
Open lid detection
Lid openning detection
Conclusion
Read moreCity waste management systems are incorporating IoT devices for a more efficient urban waste collection service. Fill level sensors, waste collection planning and analytics are more and more common in cities and businesses.
In some industries having waste monitoring devices could be really useful. A dashboard with information of the temperature/humidity of the bins could help in determining is there is risk of fire, monitoring how many times the lid is opened could help in understanding if more bins are necessary and even determine when to replace the trash cans and detecting movement could help knowing in real time when the bins are moved from their location.
This Proof of Concept is exactly focused in this, in investigation the usage of a COTS device to monitor the status of the bins in the factory and show the information in a cloud based dashboard.
ObjectiveThe objective was to understand how Octonion’s Brainium portal works and how easy is to develop a small proof of concept to:
1) Detect if the trash can lid is being opened
2) Detect if the trash can is open (using light detection) and alerts
3) Show some measurements in a dashboard
Lid opening detection was planned to be programmed using the Brainium's, zero-code, machine learning tool and the rest was planned to rely on Brainium dashboard and alerts.
Set upFirst point was to set up the device. This time I used an old Nexus 5 phone as gateway.
After signing up in https://spa.brainium.com/signup , I download and installed the Brainium app in the gateway ( The app can be found here: https://play.google.com/store/apps/details?id=com.brainium.android.gateway )
(Note: Don't forget to enable the location in your Android mobile (Gateway), and give permissions to Brainium app)
After login in in the Brainium app, I went to the Brainium Portal ( https://spa.brainium.com/login ), powered up the device (Blue led blinking) and in the equipment section asociated the SmartEdge Agile device with the Gateway.
Once the connection was ready, I could click on devices icon (https://spa.brainium.com/equipment?tab=devices) and click in my device to see a screen like the one below.
Brainium Portal: Device Info
The next step was to create a project so I was ready to develop the proof of concept.
DashboardThe first objetive was to create a simple dashboard for the bin monitoring. I wanted to add temperature (even it is internal), humidity and pressure. I created different widgets (Line charts and Gauges) to set up a dashboard like the one below.
Dashboard
The next things I wanted to test were the open lid detection and alerts.
Open lid detection
In order to detect the open lid, I used the light sensor. Basically detecting any value over 0.8 meant that the lid was open. So, in the devices section, after clicking my device, I add a new rule to the Rule panel.
Alert rule
This rule produced notifications each time the lid was open.
Alert notification
The third objetive was to test the claimed zero-code AI features, and for that I attached the sensor to the lid and trained the model opening the lid several times.
I did this clicking the Motion Recognition side icon ( https://spa.brainium.com/workspaces?tab=ai ) and creating a new workspace. In the working set I created the "Open" motion and recorded several motion sets
Training sets
After the recording and generating the model (bottom left) I started getting notications we the lid was being openned, at it is shown in the image below.
AI Notifications
This proof of concept allowed me to play a bit with the Brainium's zero-code development portal and SmartEdge Agile device. From one side, it was interesting to develop the proof of concept without writing any code, but for the other side I missed the possibility of working directly with the hardware.
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