We have had a long interest in networked sensing, the idea that information from network-connected sensors can be mined to understand environments and behaviors
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Sensing the Sensor: Estimating Camera Properties with Minimal Information
Pradipta Ghosh, Xiaochen Liu, Hang Qiu, and 3 more authors
ACM Trans. Sen. Netw. Feb 2022
Public outdoor surveillance cameras often have limited metadata describing their properties. Frequently, a public camera’s precise position, orientation, focal length, and image center are unknown; these attributes are necessary to precisely pinpoint the location of events seen in the camera. In this article, we ask: what is the minimal information needed to accurately estimate these properties for public cameras? We show, using a judicious combination of projective geometry, neural networks, and crowd-sourced annotations from human workers, that it is possible to, for example, localize 95% of the cameras in our test data set to within 12 m using a single image taken from the camera. This performance is an order of magnitude better than PoseNet, a state-of-the-art neural network that needs significantly more information than our approach, and can only estimate position and orientation (and not other properties). Finally, we show that the camera’s inferred pose and properties can help design a number of virtual sensors, all of which have good accuracy.
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Synthesis of Large-Scale Instant IoT Networks
Pradipta Ghosh, Jonathan Bunton, Dimitrios Pylorof, and 6 more authors
IEEE Transactions on Mobile Computing Feb 2021
While most networks have long lifetimes, temporary network infrastructure is often useful for special events, pop-up retail, or disaster response. An instant IoT network is one that is rapidly constructed, used for a few days, then dismantled. We consider the synthesis of instant IoT networks in urban settings. This synthesis problem must satisfy complex and competing constraints: sensor coverage, line-of-sight visibility, and network connectivity. The central challenge in our synthesis problem is quickly scaling to large regions while producing cost-effective solutions. We explore two qualitatively different representations of the synthesis problems using satisfiability modulo convex optimization (SMC), and mixed-integer linear programming (MILP). The former is more expressive, for our problem, than the latter, but is less well-suited for solving optimization problems like ours. We show how to express our network synthesis in these frameworks. To scale to problem sizes beyond what these frameworks are capable of, we develop a hierarchical synthesis technique that independently synthesizes networks in sub-regions of the deployment area, then combines these. We find that, while MILP outperforms SMC in some settings for smaller problem sizes, the fact that SMC’s expressivity matches our problem ensures that it uniformly generates better quality solutions at larger problem sizes.
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Scrooge: A Cost-Effective Deep Learning Inference System
Yitao Hu, Rajrup Ghosh, and Ramesh Govindan
In SoCC ’21: ACM Symposium on Cloud Computing, Seattle, WA, USA, November 1 - 4, 2021 Feb 2021
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Rim: Offloading Inference to the Edge
Yitao Hu, Weiwu Pang, Xiaochen Liu, and 4 more authors
In Proceedings of the 6th ACM/IEEE Conference on Internet of Things Design and Implementation, 2021 Feb 2021
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New Frontiers in IoT: Networking, Systems, Reliability, and Security Challenges
Saurabh Bagchi, Tarek F Abdelzaher, Ramesh Govindan, and 4 more authors
IEEE Internet of Things Journal Feb 2020
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Persistent Connected Power Constrained Surveillance with Unmanned Aerial Vehicles
Pradipta Ghosh, Paulo Tabuada, Ramesh Govindan, and 1 more author
In Proceedings of the IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS) Feb 2020
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Grab: Fast and Accurate Sensor Processing for Cashier-Free Shopping
Xiaochen Liu, Yurong Jiang, Kyu-Han Kim, and 1 more author
In Feb 2020
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Rapid Top-Down Synthesis of Large-Scale IoT Networks
Pradipta Ghosh, Jonathan Bunton, Dimitrios Pylorof, and 6 more authors
In Proceedings of the IEEE International Conference on Computer Communications and Networks (ICCCN) Feb 2020
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Caesar: Cross-camera Complex Activity Recognition
Xiaochen Liu, Pradipta Ghosh, Oytun Ulutan, and 3 more authors
Feb 2019
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Kestrel: Video Analytics for Augmented Multi-Camera Vehicle Tracking
H Qiu, X Liu, S Rallapalli, and 5 more authors
In 2018 IEEE/ACM Third International Conference on Internet-of-Things Design and Implementation (IoTDI) Feb 2018
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Scalability and Satisfiability of Quality-of-Information in Wireless Networks
Scott T Rager, Ertugrul N Ciftcioglu, Ram Ramanathan, and 2 more authors
IEEE/ACM Trans. Netw. Feb 2018