Le Roux, ENdiaye, MAbu-Mahfouz, Adnan MI2021-11-192021-11-192021-06Le Roux, E., Ndiaye, M. & Abu-Mahfouz, A.M. 2021. Automatic number plate recognition for remote gate automation: An edge computing approach. http://hdl.handle.net/10204/12166 .978-1-7281-9022-8978-1-7281-9023-52163-5145DOI: 10.1109/ISIE45552.2021.9576167http://hdl.handle.net/10204/12166The article proposes a gate automation system based on automatic number plate recognition (ANPR). The system uses a convolutional neural network (CNN) to identify and classify each number plate which is then compared to a database of authorized numbers before a gate is opened. Once the gate is opened an extra feature of alerting the farm settlement owner via SMS and LoRa is added. What this work tries to do is demonstrate the ability of an IoT-edge device to perform complex image processing computations simply by adding more computing resources at the edge. Edge computing suggests adding a powerful edge device to support edge devices however, we envision the extra computing power can be extended and embedded in the edge devices themselves. To demonstrate this we equip our edge device system with a single board computer to provide the needed computing resources for ANPR.AbstractenAutomatic number plate recognitionANPRConvolutional neural networkCNNConference PresentationLe Roux, E., Ndiaye, M., & Abu-Mahfouz, A. M. (2021). Automatic number plate recognition for remote gate automation: An edge computing approach. http://hdl.handle.net/10204/12166Le Roux, E, M Ndiaye, and Adnan MI Abu-Mahfouz. "Automatic number plate recognition for remote gate automation: An edge computing approach." <i>2021 IEEE 30th International Symposium on Industrial Electronics (ISIE), Kyoto, Japan, 20-23 June 2021</i> (2021): http://hdl.handle.net/10204/12166Le Roux E, Ndiaye M, Abu-Mahfouz AM, Automatic number plate recognition for remote gate automation: An edge computing approach; 2021. http://hdl.handle.net/10204/12166 .TY - Conference Presentation AU - Le Roux, E AU - Ndiaye, M AU - Abu-Mahfouz, Adnan MI AB - The article proposes a gate automation system based on automatic number plate recognition (ANPR). The system uses a convolutional neural network (CNN) to identify and classify each number plate which is then compared to a database of authorized numbers before a gate is opened. Once the gate is opened an extra feature of alerting the farm settlement owner via SMS and LoRa is added. What this work tries to do is demonstrate the ability of an IoT-edge device to perform complex image processing computations simply by adding more computing resources at the edge. Edge computing suggests adding a powerful edge device to support edge devices however, we envision the extra computing power can be extended and embedded in the edge devices themselves. To demonstrate this we equip our edge device system with a single board computer to provide the needed computing resources for ANPR. DA - 2021-06 DB - ResearchSpace DP - CSIR J1 - 2021 IEEE 30th International Symposium on Industrial Electronics (ISIE), Kyoto, Japan, 20-23 June 2021 KW - Automatic number plate recognition KW - ANPR KW - Convolutional neural network KW - CNN LK - https://researchspace.csir.co.za PY - 2021 SM - 978-1-7281-9022-8 SM - 978-1-7281-9023-5 SM - 2163-5145 T1 - Automatic number plate recognition for remote gate automation: An edge computing approach TI - Automatic number plate recognition for remote gate automation: An edge computing approach UR - http://hdl.handle.net/10204/12166 ER -25100