The safety measures in a city are of major concern to its people. A smart surveillance system is necessary to make the safety measures robust and reliable. Currently, there are many object detection methods available for image analysis. Image analysis is only possible when we can detect the number of objects in the image, type of objects, as well as their location. Image analysis methods include Fast RCNN, YOLO, region-based convolution neural network (RCNN), and so on. These object detection methods are based on deep learning (DL) techniques. Video analysis requires the detection of moving objects. These methods involve background subtraction and extracting the foreground objects for motion analysis. There are several deep learning (DL)-based methods for video analysis such as the YOLO algorithm for detecting objects in a video frame and identifying their location. This chapter describes significant object detection methods in images and video that can be used in surveillance systems to improve the safety measures in a city.
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The safety measures in a city are of major concern to its people. A smart surveillance system is necessary to make the safety measures robust and reliable. Currently, there are many object detection methods available for image analysis. Image analysis is only possible when we can detect the number of objects in the image, type of objects, as well as their location. Image analysis methods include Fast RCNN, YOLO, Region-Based Convolution Neural Network (RCNN), and so on. These object detection methods are based on Deep Learning (DL) techniques. Video analysis requires the detection of moving objects. These methods involve background subtraction and extracting the foreground objects for motion analysis. There are several Deep Learning (DL) based methods for video analysis such as the YOLO algorithm for detecting objects in a video frame and identifying their location. This chapter describes significant object detection methods in images and video that can be used in surveillance systems to improve the safety measures in a city.
A smart city aims to improve the quality of life of its citizens with the use of technology. The innovative solutions make the operations efficient and bring sustainability to mankind as well as the environment. Currently, cities across the world are on their way to become smarter by implementing smart solutions such as smart governance, smart energy, smart sanitation, and waste management, smart transportation, smart infrastructure, and smart healthcare to name a few. However, the cities overlook safety and security parameters. The use of technology helps people in many possible ways. But it has its drawbacks too. Evidently, the crimes in the cities are on rise. There are frequent incidents of traffic rule violations. So, the need for better security, and surveillance methods also arise.
The development of smart cities must ensure the safety needs of the people along with preserving the environment and ecosystem. Accordingly, a Smart City should also be a Safe City. A Safe City must adopt necessary measures to protect life, and property of people. At the same time, it should also ensure the privacy and security of data. Therefore, a smart and safe city needs to implement security and surveillance mechanisms by installing CCTV cameras. GPS-enabled vehicles help people in tracking the route they are traveling. The use of connected vehicles also enhances safety. A smart traffic management system can help in reducing traffic rule violations and prevent road accidents.
The smart security and surveillance system can help in the detection and identification of criminals, detecting suspicious activities and objects so that prompt action can be initiated. An efficient mechanism of CCTV footage analysis is also required. Smart security solutions also enable crisis management by providing early warning signs. For example, an indication of natural calamities such as floods, and cyclones can save the lives of millions of people.
Smart homes make use of many smart devices that collect large volumes of user’s data daily. The security and privacy of user’s data is also a concern that needs to be addressed. Hence, smart security solutions must also employ mechanisms to ensure the security and privacy of user’s data.
Most of the security enhancement methods rely on CCTV footage and video surveillance. Therefore, Image analysis and video analysis is an integral component of security solutions. For instance, face detection methods play important role in many smart city applications such as smart door locks, biometric attendance, and criminal identification. Similarly, video analysis is required to detect traffic light violations, smart home security, and monitoring the security in schools, malls, and other public places. Self-driving vehicles should also have sophisticated mechanisms for image and video analysis. This is because these vehicles need to recognize the objects and also their relative distance so that they can apply the brake if necessary. Object detection methods also help in preserving resources by identifying the presence of people in a room so that the appliances such as air-conditioners, lights, and heaters can be automatically turned off and on.