The goal of this project is to leverage and improve upon the capabilities of honey bees as agricultural pollinators by incorporating them into Bio-Cyber Physical systems. Rapid advances are needed to aid a dwindling agricultural workforce, increase crop yield to sustain the growing population, and provide targeted crop care to limit the need for broad pesticide treatments. These challenges may well be addressed by autonomous mobile robots and sensor networks; unfortunately, agricultural landscapes represent vast, complicated, and dynamic environments that complicate long term operation. In contrast, social insects are capable of robust sustained operation in unpredictable environments far beyond what is possible with state-of-the-art artificial systems. Colonies of honey bees are of particular interest in this project, because they are the premiere agricultural pollinator bringing in over $150 billion annually. The U.S. has an estimated 2.4 million colonies, many of whom travel the country every summer to help pollinate monocrops such as almond and corn. A colony causes pollination by dispatching tens of thousands of scouts and foragers to survey and sample kilometer-wide areas around their hive. Thus, the colony as a whole accumulates vast information about the local agricultural landscape, bloom and dearth -- information that would be very informative if available to farmers and beekeepers.

This project will leverage social insects as environmental indicators by piggybacking on their naturally existing capabilities. It involves sensors to record where bees focus their foraging activity, and mechanisms to stimulate additional foragers. This project will impact: 1) ultra-low power electronics and sensing, 2) probabilistic inference from large scale distributed data sources, 3) feedback control of biohybrid systems, and 4) gains to apiculture and entomology. The proposed bio-hybrid technology may further inform models of how bees forage in natural versus cultivated areas, and may lead to new insights on design of agricultural multi-use landscapes for improved yield. Overall, this research will improve engineers' understanding of Bio-Cyber Physical Systems able to monitor and affect the environment, and may be applicable to scenarios including search and rescue, detection of chemical spills, and targeted pollination.

To harness the capabilities of a bee colony while still providing control and sensing, the proposed work specifically involves 1) novel submillimeter flight recorders with visual scene capture and analysis, thermal and mechanical sensors, a clock, storage, processing, photovoltaic chargers and short range communications; 2) algorithms and models to estimate foraging maps, relying on bee motion models and feature extraction, merging probability density functions of observed landmarks from thousands of flights; and 3) feedback control via a bee-mimicking shaker device to recruit foragers, in turn eliciting data collection and pollination, e.g. during brief spouts of bloom that would otherwise go unnoticed by the colony. This research represents a transformative step towards a new frontier in Bio-Cyber Physical Systems, improving upon the abilities of social insects to sense and interact with the physical world, while providing data acquisition and control on par with explicitly engineered systems.

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Cornell University
United States
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