Introduction

The Wild Blueberry Harvester Sensor System aims to assist operators by offering audio and visual feedback on optimal rake height, linear speed, and rotational speed.

The system consists of two main components: a Microcontroller (MC) and a Mobile Application (MA). The MC collects data from various sensors and calculates the optimal operation parameters, which are then displayed on the MA for the operator to make informed decisions.

Components

• Arduino Giga R1 Wifi: The MC chosen for this project is the Arduino Giga R1 Wifi. This microcontroller offers essential features that support both the current project and potential future upgrades. Key reasons for choosing this MC include:

  • Open-Source Platform: The Arduino platform is well-supported with a large community of developers.

  • Connectivity: It offers Bluetooth and WiFi connectivity, crucial for reliable communication with the Mobile Application (MA).

  • Expandable: It has a large array of digital and analog pins, allowing for the addition of more sensors as needed.

• OUKITEL RT3 Android Tablet: The mobile application runs on an Android tablet. Specific features of the tablet include:

  • Cost-Effective: Android tablets offer similar capabilities to other brands but at a more affordable price.

  • Durability: The OUKITEL RT3 is designed for outdoor use, making it suitable for the rugged environment of blueberry harvesting. Features like waterproofing and drop resistance ensure reliability in various weather conditions.

  • Accessibility: With a wide range of apps and flexibility, Android tablets provide ease of use and accessibility for the operators

Key Features

• Real-Time Data Collection: Utilizes ultrasonic, hall effect, and potentiometer sensors to gather real-time data on bush height, linear speed, and rake height.

• Optimal Operation Feedback: Calculates and displays optimal rake height and rotational speed, allowing operators to adjust their equipment for maximum efficiency.

• User-Friendly Interface: The MA provides an intuitive and accessible interface, making it easy for operators to view and act on the feedback.

• Scalability and Future Improvements: Designed with a layered architecture to support future enhancements, such as additional sensors and autonomous adjustments.

Results

✅ Successful sensor data collection & transmission via Bluetooth.
✅ Optimized harvester settings through real-time data analysis.
✅ Improved modular sensor design, making future upgrades easier.
✅ Prototype tested & validated, showing promising results for future iterations.
✅ Presented at the Steering Committee in front of the members of the Wild Blueberry Commission of Maine

Checkout our Github!