Low-Cost Aerial Imaging for Small Holder Farmers
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Low-Cost Aerial Imaging for Small Holder Farmers Vasuki Narasimha Swamy* Akshit Kumar* Rohit Patil* UC Berkeley IIT Madras PESIT Aditya Jain* Zerina Kapetanovic* Rahul Sharma* IIIT Delhi University of Washington CMU Deepak Vasisht* Manohar Swaminathan Ranveer Chandra MIT Microsoft Microsoft Anirudh Badam Gireeja Ranade* Sudipta Sinha Microsoft University of California Berkeley Microsoft Akshay Uttama Nambi S N Microsoft CCS CONCEPTS and use that to develop an interactive mobile phone application • Human-centered computing → Ubiquitous and mobile com- that provides the user instant feedback to guide users to efficiently puting systems and tools; traverse large areas of land. We use computer vision algorithms to stitch orthomosaics by effectively countering wind-induced motion KEYWORDS of the camera. We have used TYE for aerial imaging of agricultural land for over a year, and envision it as a low-cost aerial imaging Aerial Imagery, Mobile Systems for Sustainability, Innovative Mo- platform for similar applications. bile Sensing ACM Reference Format: 1 INTRODUCTION Vasuki Narasimha Swamy*, Akshit Kumar*, Rohit Patil*, Aditya Jain*, Ze- Unmanned Aerial Vehilces (UAVs) and drones have gained tremen- rina Kapetanovic*, Rahul Sharma*, Deepak Vasisht*, Manohar Swaminathan, Ranveer Chandra, Anirudh Badam, Gireeja Ranade* , Sudipta Sinha, and Ak- dous traction as a tool for enabling digital agriculture [13, 25, 31, 32]. shay Uttama Nambi S N. 2019. Low-Cost Aerial Imaging for Small Holder In contrast to satellites, which typically captures only about 10 Farmers. In ACM SIGCAS Conference on Computing and Sustainable Societies clean images from seeding to harvest [3], a drone can be flown (COMPASS) (COMPASS ’19), July 3–5, 2019, Accra, Ghana. ACM, New York, on-demand, and can get very high resolution NY, USA, 11 pages. https://doi.org/10.1145/3314344.3332485 imagery. They can also be Abstract – Recent work in networked systems has shown that mounted with multi-spectral or using aerial imagery for farm monitoring can enable precision hyper-spectral cameras to ob- agriculture by lowering the cost and reducing the overhead of tain detailed imagery of the large scale sensor deployment. However, acquiring aerial imagery farms [14]. A recent research in requires a drone, which has high capital and operational costs, networked systems [32] takes often beyond the reach of farmers in the developing world. In this the aerial imagery a step fur- paper, we present TYE (Tethered eYE), an inexpensive platform ther, by combining aerial im- for aerial imagery. It consists of a tethered helium balloon with a agery with ground sensor data, custom mount that can hold a smartphone (or a camera) with a to create detailed precision maps battery pack. The balloon can be carried using a tether by a person for a farm, such as for soil tem- or a vehicle. We incorporate various techniques to increase the perature, pH, and soil moisture, operational time of the system, and to provide actionable insights which are then used to enable even with unstable imagery. We develop path-planning algorithms low-cost precision agriculture. While such systems work well *The work was done when the authors were at Microsoft. in the developed countries, the Permission to make digital or hard copies of all or part of this work for personal or startup cost of buying a commer- classroom use is granted without fee provided that copies are not made or distributed cial quadrotor (around $ 1000) for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the is prohibitive for farmers in de- author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or veloping countries. Additionally, republish, to post on servers or to redistribute to lists, requires prior specific permission the lack of technical knowledge and/or a fee. Request permissions from [email protected]. COMPASS ’19, July 3–5, 2019, Accra, Ghana among the farmers in develop- © 2019 Copyright held by the owner/author(s). Publication rights licensed to the ing countries means that they of- Association for Computing Machinery. ten need specialized technicians Figure 1: Mobile TYE: A user ACM ISBN 978-1-4503-6714-1/19/07...$15.00 images a farm using Mobile TYE https://doi.org/10.1145/3314344.3332485 to operate them. This implies COMPASS ’19, July 3–5, 2019, Accra, Ghana that for large parts of the world, digital agriculture techniques than past frames, and transmit only those frames which might cor- remain out of bounds. respond to some form of event or motion. However, this doesn’t In this paper, we address this problem by designing an alternative work for TYE, since wind-induced motion causes most frames to aerial imagery platform, that has low capital investment, low oper- be different from past frames. An alternative is to use complex ational costs and high resolution. We present our system, TYE (for object detection and motion tracking vision techniques to identify Tethered eYE). TYE uses lighter-than-air gas (such as helium) filled frames in which moving objects were observed. However, these balloons to provide lift to an existing imaging infrastructure (such techniques require high compute power, and are either not feasible as a smartphone). The balloon is held using a tether at heights from on a smartphone or take too much time to offset the power savings. 50 ft to 150 ft depending on the required resolution. The design of In contrast to these approaches, we leverage an important insight TYE has been motivated by the strong penetration of smartphones to design a low complexity frame selection technique. As the bal- in the developing world [23], combined with enhanced imaging loon drifts, all pixels in the frame captured by the camera drift in a capabilities of such smartphones. direction opposite to the balloon. However, if something changes TYE operates in two modes. First, it has a mobile mode, wherein in the environment, the pixels corresponding to the change must it operates like a UAV and the tether is held by a person who walks have a different drift than the majority of the pixels corresponding around the field. In this mode, the imagery can be used to generate to static objects. By identifying these outliers, i.e. pixels that have precision maps. As our aerial imagery platform design does not a drift different from the average drift of the frame, we can iden- require power to stay afloat, it enables an additional static mode, tify frames that have an interesting event and only transmit them, where the balloon is tethered to a stationary point. In this mode, the thereby reducing the power required for data transmission. balloon can provide the farmer with long term surveillance imagery We have implemented TYE as a software-hardware system, using of the farm. While the design of TYE is simple, the challenge lies helium balloons and evaluated them in farms across US and India. in delivering high-fidelity, interpretable aerial imagery. To enable The main contributions of this paper are: long-duration, low cost, large-area aerial imagery, we must address • We design two modes of TYE: mobile and static which are useful three fundamental aspects: for on-demand imaging of large areas and long-duration imaging (i) Wind Induced Variability: Unlike UAVs, low winds cause sig- for a single area respectively. nificant changes in the position (lateral motion and rotation) of • We design new software-hardware mechanisms to reduce wind- the camera that is capturing aerial images using balloons. These induced variability in captured imagery and present a consistent unpredictable changes in camera viewpoint due to wind makes view to the farmer in spite of frequent camera motions. imagery difficult to view and analyze. Our solution to this problem • We build a novel path-planning algorithm that captures the area is two-fold: (a) we design a custom mount for the payload that can being imaged and intelligently mitigates the effects of wind – reduce wind-induced variability, and (b) we leverage gyroscopes effectively reducing the time needed to image a given area. (present in most smartphones) to eliminate frames with extreme • We design novel low-complexity anomaly-detection algorithms motion while ensuring sufficient coverage. We then use techniques and custom hardware to enhance the uptime of the system. from computer vision to correct for the remaining camera motion While a detailed evaluations of TYE are in sections 6 and 8, we list in software; thus producing consistent views for the user as if the the important results here: camera was stable, despite arbitrary camera motions. (ii) Spatio-temporal Coverage: Spatial mapping of a farm re- • The hardware modifications reduce the leakage through the sur- quires TYE to be maneuverable like drones. Thus, mobile-TYE face of the balloon by ≈ 90%. requires a person to move the balloon. In our experiments, we • The area imaged in mobile mode using TYE’s app and path plan- observe that users fail to ensure complete coverage of an area if ning algorithm is 88:2% of the area of interest as opposed to they rely purely on their intuition. This is due to the mismatch 78:5%, when the user is not using the app. The users walking between a person’s 2D trajectory and the balloon’s 3D trajectory. have to walk 25.2% more steps without the app to guide them. Furthermore, some areas might be inaccessible to the user due to • The intelligent-frame selection algorithm reduces the average obstructions. For example, in farms, plots are interspersed with frame transmissions by 94% and the overall battery consumption trees, bunds, ponds, and electrical poles etc. To address these con- by 67-88% depending on the image resolution.