Identifying Beehive Frames Ready For Harvesting

Harvesting of honey is a laborious job which requires the daily inspection of every frame within every hive of every apiary. Apiaries are easily scalable via the addition of new hives or the addition of expansion boxes to existing hives but the scaling of human labor to meet the added work needed to inspect, harvest, and maintain the added frames is costly and often nonexistent. Existing Internet of Things (IoT) beekeeping and monitoring systems on the market are very costly and do not provide per-frame information to beekeepers. Although they are successful in generating a slew of useful information regarding the strength, condition, and even overall honey yields of a hive over time, they fall short in enabling beekeepers to know exactly which frames are ready for harvesting without a physical inspection of each. Therefore, they neither contribute to the labor reduction associated with harvesting nor are they effective in the prevention of swarming, a condition where a hive colony reproduces via exiting the hive and leaving behind the larvae of the next generation - thus halting honey production. The only way to truly reduce honey harvest labour and swarming is to collect per-frame weight data which is a complex and costly task and has therefore been avoided in existing solutions. Our initial results in collecting per-frame weight have confirmed the complexity and costliness of this task though have also provided us with a clear path to the reduction of both the complexity and cost of a per-frame harvesting scheduler. We utilized low cost off-the-shelf force sensors along with a mathematical model for data normalization which produces accurate data. However, the complexity and cost must still be reduced via the design and development of new custom sensors in order to create a viable and marketable product.