Abstract
In this paper, a novel visual image real-time detection LSE-Yolo neural network is presented, which is in artificial intelligence-based Internet of Things for smart cites and smart homes. Despite the great achievements that have been acquired in image detection, the issue of visual image real-time detection combined with privacy data protection to serve for smart cities and smart homes has been overlooked. The technique we applied in our study is referred to as visual object detection, which can contribute to more healthy and comfortable life. When several studies have been carried out to test the validity, it is suggested that our proposed LSE-Yolo neural network has better performance in image real-time detection based on AIoT for smart cities and smart homes. And it is similar to state-of-the-art. The fruitful work has made great contributions to our present understanding of the visual image detection serving for smart cities and smart homes.
Highlights
To meet the needs of modern smart cities and homes, visual system in computer vision applied in smart cities and smart homes has become a hot topic in artificial intelligence and Internet of Things (AIoT)
It is found that our proposed LSE-Yolo neural network in artificial intelligence-based Internet of Things for smart cities and smart homes has better performance than other common neural networks
The comprehensive of the proposed LSE-Yolo is highly consistent with the prediction of the theoretical model, which is suitable for smart cities and smart homes
Summary
With the improvement of residents’ living standards and consumption power, the traditional life has been changed to the life with science and technology, which can make it more healthy, fast, convenient, and comfortable. Image detection in AIoT has attracted much attention from the academia, which can serve for smart cities and smart homes. There have been several studies highlighting object detection for smart cities and smart homes [1–8] in recent years. Object detection plays an important role in the visual system application in AI-based for smart cities and homes. The common object detection algorithms can be classified into two categories: one is traditional detectors and the other is deep learning-based detectors. It has become a trend that object detection algorithms served for smart cities and homes. Khan et al [3] in 2017 presented the detection of people through computer vision in the Internet of Things scenarios to improve the security in smart cities, smart towns, and smart homes. In 2019, Garcia et al [1] proposed to perform object detection mechanism based
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Free) 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a call
