Abstract
The objective of this chapter is to propose a model of an automated city crime-health management that can be implemented in future smart cities of developing countries. The chapter discusses how a suitable amalgamation of existing technologies such as IoT, artificial intelligence, and machine learning can output an efficient system of unmanned city management systems, thereby facilitating indirect engendering of innovative scopes for technology workers and researchers and alleviating the living standards within the city fabrics, catalyzing infrastructure development. In this chapter, the authors have structured an ideal UAV-matrix layout for city fabric surveillance built over the scopes of artificial intelligence. Succinctly, this chapter provides a platform that would galvanize the possibilities and that could be reimagined to structure a more resourceful working model of new emerging smart cities and enlighten the settings of existing ones.
TopIntroduction
In the present scenario of urban habitats, the cities have become chaotic. By 2050, 68% of the population would be residing in the cities. (United Nations, 2019) If things go according to the current scenario of city development, the city would not be able to sustain this tremendous amount of human population. A ‘City’ is a culmination of the holistic aspirations of its inhabitants. A city should cater to the demands and necessities regarding victuals, security, healthcare, navigation, and rights. After-all the evaluation of the city design is based entirely on the forward and backward interaction between the city and its users. However, every single task within delivering services as per the demands of its users is not a fluent task, instead, it is laborious and requires rational decision-making units. Hence, to manage and accomplish such tremendous number of tasks that all together build up to a happy and smart city, the management is exposed to challenging aspects like Precision, Duration, Accuracy, Timeliness, and Consistency. But can humans alone tackle these obstacles to build such an ideal city? Or is it smart enough to waste much of human resources in just the maintenance of the city fabric?
In the modern times, the age of Artificial Intelligence, IoT, and robotics, implementation of such technology in the management systems of the city fabrics could drastically solve the challenging aspects in delivering each of its citizens, their demands. These multitasking technologies have proved to be both veracious and timely. Why are AI and robotics more than the existing technologies in city management? They simply work by inputting, processing and outputting, but through the implementation of IoT, and machine learning-the system now can review itself and correct the existing algorithms.
This chapter is an endeavor to give a thought regarding future degree, potential conceivable outcomes and issues concerning instalment of UAV (Unmanned Aerial Vehicles) Systems in the city fabric and how might it get change the lives of the general city population sooner rather than later in significance to create a better bond between the city and its users. The UAV system is simply a 3D matrix over the city fabric managed and directed by its CPU unit, performing tasks like monitoring, reporting, actions, and learning. The scale and complexity of the purpose can vary from basic food and package delivery to health and crime monitoring. Currently, the governing bodies of certain countries have framed a set of permits and privacy laws. Many works have been done on UAV-based Traffic Analysis, UAV-based Package delivery (Amazon Drone Delivery: Prime Air), UAV surveying, etc. Scopes like UAV based healthcare and crime monitoring using motion tracking and human activity recognition will be examined and discussed in this chapter.
Heinous Activities that are Remote and Inaccessible by the Supervisors and Inceptors by a Specific Time
What happens if a region of the city is at the moment with the absence of human at night, and someone has had a heart attack or dehydrates to faint and is helpless? How do we notice such events and solve the case? What happens if a Crime is occurring in dark corners of a city, where human presence is absent? How can be such activities recognized and controlled with necessary action? What if there is a city where such aspects are well supervised and maintained? Won’t the users get a subconscious feeling of safety? Won’t there be a drastic decrease in crime rate itself, if the users know that they are being watched? Won’t there be fewer health breakdowns of the citizens if they are diagnosed immediately?
Traditional Surveillance
The traditional surveillance methods include the implementation of a security camera or a network of cameras, a control room for monitoring and humans working in the control room to take the required decisions. Even though the technology proves to be effective in crime management, the challenging aspects like precision, duration, accuracy, timeliness, and consistency are not efficiently tackled.
Key Terms in this Chapter
Activity Dataset in Cloud Database: The database containing catalogs of human activity classification, thermal-human behavioral maps, gesture datum, etc., that will be used by the algorithms to classify and predict heinous activities.
Motion Energy Image: It is a grayscale static image where; the frames of a video clip are collapse into single. This is used to predict and recognize the subjects in a video footage.
City Fabric: City Fabric is the fabric of space in a city that excludes all the building envelopes. City fabric includes the Urban Infrastructures, Streets, Morphology etc. Usually this is the space that is maintained by the public governmental services.
Human Activity Prediction: Ability to predict the future event that is going to happen, from a given sequence of image or video footage.
UAV Matrix: The drone matrix is the three-dimensional spatial network of actively functioning drones hovering above the city fabric, performing the task of surveillance, working together. They can be labeled by their spatial coordinates.
Heinous Activities: Activities that are suspicious in nature, which can be used to predict the occurrence of unpleasant event. For example, in a crime scene, when a criminal is going to perform a crime, the all set of activities that happens just before he performs the crime, like lifting up weapons, moving towards victim in a suspicious manner, etc.
Motion History Image: It is a grayscale static image, which help in understanding the progress of subjects in a video footage. In this image, the frames of a video clip are collapse into single, with the brightness of the frames increasing the time stamps of the frame in the video. This is used to predict motion and motion flow.
Human Activity Recognition: Ability to classify and recognize human activity with the help of image sequences or a video footage.