13. Applications and implications¶
This week I worked on defining my final project idea and started to getting used to the documentation process.
- What will it do?: Automate switching of stop lights based on traffic volume. I aim to make a scaled down prototype for the same
The signal unit will determine the number of vehicles / traffic volume using cameras and ultrasonic sensors. The signal housing should be rain proof and so should the sensors. The sensors should have high accuracy and range since the signal will be mounted far from the vehicles.
- What will you design?¶
Traffic stop light and pedestrian crossing lights PCBs, light housing and sensor housing.
What materials and components will be used? Where will they come from?¶
|NeoPixel RGB 64||Mouser||23.5|
|Resistors & other components||Fablab||3|
|Nuts & bolts||Ferreria||0.5|
- What parts and systems will be made?¶
PCBs, light housing and sensor housing. The system will detect cars and send data to a processor to determine which direction has most cars every 5 seconds. Based on this data, another board will tell the LEDs to light up accordingly.
- What processes will be used?¶
3D printing for processor housing, CNC milling for PCB, laser cutting for light housing, 3d printing for overall housing and acrylic heat moulding for light luminaire(optional).
- What questions need to be answered?¶
- How effective is the camera AI vision on a Raspberry Pi programmed in Python?
- How does the final product relate to its environment in terms of production, feasability, visibility and anti frost/ fog capability.
- How does the new design apply to people with disabilities?
- How will it be evaluated?¶
Vehicles wait periods are shorter, on average, than those at a regular timer based intersection
Signals are more modular and less prone to failure. Even during failure on a module, another module serving the same lane should be able to compensate for the failed unit.