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Smart city article details
| Title | Deep Learning Techniques For Image Recognition In Iot-Enabled Surveillance Systems |
|---|---|
| ID_Doc | 17919 |
| Authors | Dankan Gowda V.; Vishnu Tej Y.; Potharaju V.S.; Jakkidi P.R.; Sharma A.; Sudhakar Reddy N. |
| Year | 2024 |
| Published | 2024 Asian Conference on Intelligent Technologies, ACOIT 2024 |
| DOI | http://dx.doi.org/10.1109/ACOIT62457.2024.10939203 |
| Abstract | This paper proposed an improved method that can be used in the identification of images within IoT based surveillance systems through the use of deep learning techniques especially the CNNs. The growth of concern and complexity therefore entails massive feeding from bursts of data from surveillance cameras, hence the need for reliable algorithms for processing the data in real-time with reasonable accuracy. The described system can be described as inclusive of IoT devices communicating with edge computing and cloud services for the purpose of scalability and performance enhancement. In this study, a very sophisticated experimental setup was employed; the authors used a number of datasets for surveillance purposes to evaluate the model. The results revealed that the segments of the method achieve a high accuracy and are continuously running through data in diverse surveillance scenarios while also being scalable. In the results section, we realized that CNN model was able to handle various environmental conditions such as; extreme lightening and occlusion. On the basis of the above mentioned data, it will be possible to suggest that this approach is rather superior compared to the other conventional approaches and therefore can be suggested as the possible solution of the modern conditions of surveillance. It thus provides platform for the advancement of intelligent surveillance system for use in smart city, security and safety application. © 2024 IEEE. |
| Author Keywords | Convolutional Neural Networks; Deep Learning; Edge Computing; Image Recognition; IoT; Real-Time Processing; Security; Surveillance Systems |
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