View Proposal

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Proposer

Chee Een Yap

Title

Intelligent Beehive Monitoring and Management System with Zero-Shot Learning

Goal

To develop an intelligent IoT-based beehive monitoring system that utilizes sensors, computer vision, and Zero-Shot Learning to provide real-time intruder detection, and hive performance tracking, enabling proactive beehive management and improved colony health.

Description

Stingless bees (meliponines) are vital pollinators and honey producers in tropical and subtropical regions. Stingless bee honey is recognized as a superfood due to its high antioxidant content and potential health benefits. However, beekeepers are facing threats from hive theft, driven by the high value of honey production. Other than theft, beekeepers also need to protect the beehives from animal threats, including bears and mice, which can damage hives and consume honey. To enhance the system's intelligence, Zero-Shot Learning is employed to identify previously unseen intruders or objects without requiring extensive training data. The collected data are transmitted to a cloud platform or mobile dashboard, allowing beekeepers to remotely monitor hive conditions and receive alerts when abnormal situations are detected.

Resources

Background

IOT, microcontroller programming, Arduino, Weight Sensor, Acoustic Sensor, GPS sensor, temperature & humidity sensor

Url

Difficulty Level

Moderate

Ethical Approval

None

Number Of Students

1

Supervisor

Chee Een Yap

Keywords

iot, microcontroller programming, arduino, weight sensor, acoustic sensor, gps sensor, temperature & humidity sensor

Degrees

Bachelor of Science in Computing Science