winest:start
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winest:start [2018/07/20 12:47] dmeyer [Wireless Resources In Progress] |
winest:start [2018/07/22 17:17] (current) suman [An Example Application: Trellis] |
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| - | **WiNEST provides new and unique opportunities for experimentation across client devices, edge devices and in-network compute resources in a large, city-wide geographical area typical to a mobile network operator or wireless ISP. In cooperation with our industry partner, 5Nines Data, we expect to cover an area as large as 60 square miles within the City of Madison, as well as some nearby suburban and semi-rural areas.** | + | WiNEST provides new and unique opportunities for experimentation across client devices, edge devices and in-network compute resources in a large, city-wide geographical area typical to a mobile network operator or wireless ISP. In cooperation with our industry partner, 5Nines Data, we expect to cover a large area across the city of Madison. |
| ===== WiNEST Architecture ===== | ===== WiNEST Architecture ===== | ||
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| - | ===== How to access ParaDrop Resources ===== | + | ===== How to access ParaDrop gateways in the WiNEST infrastructure ===== |
| Here we will cover the basic idea of how to access ParaDrop resources. | Here we will cover the basic idea of how to access ParaDrop resources. | ||
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| - | ===== An Example Application: Trellis ===== | + | ===== Anatomy of an Application: Trellis ===== |
| We developed a low cost Wi-Fi-based in vehicle monitoring and tracking system that can passively observe mobile devices and provide various analytics about people both within and outside a vehicle which can lead to interesting population insights at a city scale. Our system leverages WiNEST architecture and runs on a vehicle-based edge computing platform. | We developed a low cost Wi-Fi-based in vehicle monitoring and tracking system that can passively observe mobile devices and provide various analytics about people both within and outside a vehicle which can lead to interesting population insights at a city scale. Our system leverages WiNEST architecture and runs on a vehicle-based edge computing platform. | ||
| The vehicle-based edge computing platform provides computing and storage resources which allow us to process massive amount of data in a timely manner. Trellis allows operators to collect various information and conduct spatial-temporal analytics in real time. With the help of WiNEST and ParaDrop, various relevant transit analytics, such as popular origin-destination stations, occupancy of vehicles, pedestrian activity trends, can be quickly derived on-board and sent back to transit operators without incurring high data requirements from the vehicles. What’s more, it is easy to deploy and manage such applications in multiple vehicles across a whole city using WiNEST and ParaDrop. | The vehicle-based edge computing platform provides computing and storage resources which allow us to process massive amount of data in a timely manner. Trellis allows operators to collect various information and conduct spatial-temporal analytics in real time. With the help of WiNEST and ParaDrop, various relevant transit analytics, such as popular origin-destination stations, occupancy of vehicles, pedestrian activity trends, can be quickly derived on-board and sent back to transit operators without incurring high data requirements from the vehicles. What’s more, it is easy to deploy and manage such applications in multiple vehicles across a whole city using WiNEST and ParaDrop. | ||
winest/start.1532108825.txt.gz · Last modified: 2018/07/20 12:47 by dmeyer
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