運用深度學習攝影機之智慧保全服務系統的研究

Study of Smart Security Service System Based on Deep Learning Camera

陳泓羲(HONG-XI CHEN)

指導教授 ： 廖珗洲

朝陽科技大學/資訊學院/資訊工程系/碩士(2020年)

摘要

AI深度學習的浪潮席捲而來，各大企業都持續推出各種深度學習的平台，如：GCP (Google Cloud Platform)、Microsoft Azure、AWS (Amazon Web Services)等，提供更快的方式來導入深度學習技術，雖然這些深度學習平台快速拉近AI技術與應用領域的距離，但是網路傳輸延遲與服務費用支出也間接限制深度學習技術的拓展，為了克服上述問題，Amazon推出了AWS DeepLens一台可運行深度學習模型的攝影機，可以在攝影機高清視訊上進行深度學習模型運算，將深度學習擴展到邊緣運算(edge computing)的範疇。
基於上述的技術發展，本研究透過產學合作計畫將AWS DeepLens導入保全業，目前保全業的影像保全服務中，監視攝影機是做為錄影存證與事後追查的用途，本研究使用AWS DeepLens取代傳統的監視攝影機，藉由深度學習攝影機運行深度學習模型來執行物件辨識，並且確認是否吻合設定的時間地點物件類型等條件，一旦吻合就會發送通知與影像到合作企業的管制中心。透過本研究的成果來展示運用DeepLens來提升影像保全的服務品質與效率，並降低導入深度學習技術的成本。

關鍵字

邊緣運算 ； 監視系統 ； 圖形識別 ； 人工智慧 ； 深度學習

並列摘要

Deep learning is rapidly emerging technology of AI (Artificial Intelligence) field. Many world’s leading companies announce their own deep learning platforms, such as GCP (Google Cloud Platform), Microsoft Azure, AWS (Amazon Web Services), and so on. These platforms provide a fast way to utilize deep learning technology. Although deep learning platforms shorten the distance between the technology and applications, the transmission latency and service cost limits the extension of the application domains. In order to overcome the above problems. AWS DeepLens is a camera that runs deep learning models. It can perform deep learning computing on HD video for real time, i.e., edge computing paradigm.
According to the above technology trend, AWS DeepLens are integrated into the security industry in this study. Video security is one of important services in security industry. However, video cameras are mainly used for recording and reviewing after some security events. AWS DeepLens are customized to be video sensors. They can be installed in various locations for real-time event triggering. These sensors are seamlessly integrated into the security control center of the cooperative company. The results of this study demonstrate the service quality and efficiency of the video security service is improved and the integration cost of deep learning technique is reduced.

並列關鍵字

surveillance system ； pattern recognition ； artificial intelligence ； deep learning ； edge computing

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