Transfer-Once-For-All: AI Model Optimization for Edge
Achintya Kundu, Laura Wynter, et al.
EDGE 2023
We present a novel and effective method for determining the placement of sensors so as to be able to satisfy probabilistic constraints on the time-to-detection of an incident. Indeed, with the wealth of real-time traffic data available today, an important new goal of intelligent traffic management systems is incident detection with time-to-detection guarantees, in particular on expressways with large distances between sensors. This goal drives investment decisions in new sensor deployment, hence making the topic a pressing need for traffic management. The method we provide makes use of a probabilistic formulation of traffic behavior and incident localization to determine the minimum spacing of sensors needed to achieve the time-to-detection goal with a specified probability.
Achintya Kundu, Laura Wynter, et al.
EDGE 2023
Jingrui He, Wei Shen, et al.
IJCAI 2013
Yiannis Kamarianakis, Wei Shen, et al.
Appl Stochastic Models Bus Indus
Shiau Hong Lim, Yeow Khiang Chia, et al.
TENCON 2016