WORKING WITH AI COPILOTS:

1. Identifying Sensors for the Shaker Device

Prompt:
"I need to identify suitable sensors for detecting tilt and providing tactile feedback in a 'Shaker' device. Can you suggest options for sensors and how they can integrate with a Particle Photon?"

Interaction:
The AI suggested using a ball tilt sensor to detect tilt, which could be easily interfaced with a Particle Photon. For tactile feedback, it recommended using a solenoid to provide physical response when the tilt is detected. It also suggested incorporating a proximity sensor for additional interaction capabilities.

Outcome:
The AI helped identify components that suited the device’s requirements, and I was able to source a ball tilt sensor and solenoid for the prototype.

Value:

• Sensor Recommendations: The AI helped narrow down the most suitable sensors, streamlining the component selection process.
• Integration Tips: The AI provided simple integration ideas, ensuring smooth connectivity between sensors and the Particle Photon.

Challenge:
Understanding how to calibrate the sensors for precise feedback (e.g., ensuring the solenoid response was appropriate for the tilt) required further exploration.

2. Circuit Design for Tilt Sensor

Prompt:
"How do I wire a ball tilt sensor to a Particle Photon and control a solenoid to provide tactile feedback when the sensor detects tilt?"

Interaction:
The AI recommended connecting the ball tilt sensor to the Photon with a 10kΩ pull-down resistor and controlling the solenoid with an NPN transistor, with a flyback diode to protect against voltage spikes.

Outcome:
The circuit worked seamlessly, and I was able to control the solenoid based on sensor input.

Value:

• Clear Circuit Logic: AI’s step-by-step guidance was easy to follow and implemented quickly.
• Practical Protection: The flyback diode suggestion was essential for preventing solenoid damage.

Challenge:
Fine-tuning sensor sensitivity for precise feedback required manual adjustments.

What Worked Well:

• Efficient Component Selection: AI quickly identified suitable sensors and components.
• Fast Prototyping Support: Circuit suggestions allowed for rapid testing.

What Was Challenging:

• Achieving precise sensor calibration and feedback required additional manual work.