CPS: Medium: Leveraging Honey Bees as Bio-Cyber Physical Systems

该项目的目标是利用和提高蜜蜂作为农业传粉者的能力，将它们纳入生物网络物理系统。需要迅速取得进展，以帮助不断减少的农业劳动力，提高作物产量以维持不断增长的人口，并提供有针对性的作物护理，以限制对广泛农药治疗的需求。自主移动机器人和传感器网络可以很好地解决这些挑战；不幸的是，农业景观代表着广阔、复杂和动态的环境，使长期运作复杂化。相比之下，群居昆虫能够在不可预测的环境中稳健地持续运作，这远远超出了最先进的人工系统所能做到的。蜂群对这个项目特别感兴趣，因为它们是主要的农业传粉者，每年带来超过1500亿美元的收入。据估计，美国有240万个蜂群，其中许多蜂群每年夏天都在全国各地旅行，帮助为杏仁和玉米等单一作物授粉。一个蜂群通过派遣数以万计的侦察兵和觅食者对蜂巢周围一公里宽的区域进行调查和取样来进行授粉。因此，蜂群作为一个整体积累了大量关于当地农业景观、开花和枯死的信息——如果农民和养蜂人可以获得这些信息，这些信息将是非常有用的。该项目将利用社会性昆虫的自然存在能力，将其作为环境指标。它包括记录蜜蜂集中觅食活动的传感器，以及刺激其他觅食者的机制。该项目将影响：1)超低功耗电子和传感，2)大规模分布式数据源的概率推断，3)生物杂交系统的反馈控制，以及4)养蜂业和昆虫学的收益。提出的生物杂交技术可以进一步为蜜蜂在自然和栽培地区如何觅食的模型提供信息，并可能为农业多用途景观的设计提供新的见解，以提高产量。总的来说，这项研究将提高工程师对能够监测和影响环境的生物网络物理系统的理解，并可能适用于包括搜索和救援，化学泄漏检测和定向授粉在内的场景。为了利用蜂群的能力，同时仍然提供控制和传感，建议的工作具体涉及1)新型亚毫米飞行记录仪，具有视觉场景捕获和分析，热传感器和机械传感器，时钟，存储，处理，光伏充电器和短距离通信；2)基于蜜蜂运动模型和特征提取的觅食地图估计算法和模型，融合数千次飞行中观测到的地标的概率密度函数；3)通过模拟蜜蜂的震动装置进行反馈控制，以招募觅食者，进而引发数据收集和授粉，例如在短暂的开花期间，否则会被蜂群忽视。这项研究代表了向生物网络物理系统的新前沿迈出的变革性一步，提高了社会性昆虫感知和与物理世界互动的能力，同时提供了与明确工程系统相当的数据采集和控制。

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.