Intelligent Traffic Monitoring with Hybrid AI

• URL: http://arxiv.org/abs/2209.00448v1
• Date: Wed, 31 Aug 2022 17:47:22 GMT
• Title: Intelligent Traffic Monitoring with Hybrid AI
• Authors: Ehsan Qasemi, Alessandro Oltramari
• Abstract summary: We introduce HANS, a neuro-symbolic architecture for multi-modal context understanding. We show how HANS addresses the challenges associated with traffic monitoring while being able to integrate with a wide range of reasoning methods.
• Score: 78.65479854534858
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Challenges in Intelligent Traffic Monitoring (ITMo) are exacerbated by the large quantity and modalities of data and the need for the utilization of state-of-the-art (SOTA) reasoners. We formulate the problem of ITMo and introduce HANS, a neuro-symbolic architecture for multi-modal context understanding, and its application to ITMo. HANS utilizes knowledge graph technology to serve as a backbone for SOTA reasoning in the traffic domain. Through case studies, we show how HANS addresses the challenges associated with traffic monitoring while being able to integrate with a wide range of reasoning methods

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