Название: AI and IoT for Smart City Applications
Автор: Vincenzo Piuri, Rabindra Nath Shaw
Издательство: Springer
Серия: Studies in Computational Intelligence
Год: 2022
Страниц:
Язык: английский
Формат: pdf (true), epub
Размер: 49.1 MB

This book provides a valuable combination of the relevant research work on developing a smart city ecosystem from the Artificial Intelligence (AI) and Internet of Things (IOT) perspective. The technical research works presented here are focused on a number of aspects of smart cities: smart mobility, smart living, smart environment, smart citizens, smart government, and smart waste management systems as well as related technologies and concepts. This monograph offers critical insight into the key underlying research themes within smart cities, highlighting the limitations of current developments and potential future directions.

Human society is rapidly moving towards smart cities which provide better quality of life to its citizens with the help of advanced technologies like IOT, Artificial Intelligence, cloud computing, blockchain, etc., in the area of transport, traffic management, environment, interaction with government, and even in the local economy. Because of the comfortable lifestyle and digital security, maintaining a system is needed for time-saving life. Smart city is bringing a cloud-connected system that revolves around the smart city ecosystems; whether they are smart homes, smart factories, smart hospitals, smart public places, smart shopping malls, smart traffic systems, smart waste management systems, or UAVs and AGVs. Therefore, a lot of advanced technologies are associated to develop the smart city ecosystem which needs a lot of research in the area of smart city.

Smart Drone Controller Framework—Toward an Internet of Drones: There has been an increasing trend to use multiple drones to cooperate autonomously beyond visual line-of-sight missions such as remote services, digital governance and planning, control of safety and security in a smart nation/smart city. In addition, Machine Learning (ML) has emerged as a key enabler to achieve efficiency in missions such as object detection and intruder detection. In this context, most of the commercially off-the-shelf Wi-Fi drones have limited resources and do not offer any firmware customization; these inherent limitations and technical gaps highlight the need for a software-based smart controller framework to realize support for a team of autonomous drones working together as an Internet of Drones (IoD). This can form the basis for strategic management of new Smart Cities that aim to optimize resources utilization and autonomize services. In this chapter, we present a preliminary architectural design to support needed capabilities and features of a cross-platform Smart Drone Controller (SDC) framework. An SDC framework supports a deployed team of Wi-Fi-based drones to conduct assigned missions collaboratively. The SDC’s ML engine has an option to choose algorithms according to the assigned mission. Overall, our SDC framework prototype improves the reliability of the team-based mission and enables a mixed selection of commercial drones to be deployed remotely and collaboratively as an IoD to create positive impact in service autonomy offered to smart city residents. This chapter details framework’s implementation and results with multiple Tello Edu drones assigned to an intruder drone detection mission.

Contents:
Smart Drone Controller Framework—Toward an Internet of Drones
Building of Efficient Communication System in Smart City Using Wireless Sensor Network Through Hybrid Optimization Technique
Estimation of Range for Electric Vehicle Using Fuzzy Logic System
Traffic Light Control Using RFID and Deep Reinforcement Learning
Driver Drowsiness Alert System Using Real-Time Detection
Traffic Control System for Smart City Using Image Processing
Visual Perception for Smart City Defense Administration and Intelligent Premonition Framework Based on DNN
Application of AI/IoT for Smart Renewable Energy Management in Smart Cities
Eye-Gaze Based Hands Free Access Control System for Smart City Public Interfaces
Reliability Analysis in Cyber-Physical System Using Deep Learning for Smart Cities Industrial IoT Network Node
Multi Robot Environment Exploration Using Swarm
AI and Blockchain for Healthcare Data Security in Smart Cities
Towards the Sustainable Development of Smart Cities Through Cloud Computing
Anomalies Detection on Attached IoT Device at Cattle Body in Smart Cities Areas Using Deep Learning




ОТСУТСТВУЕТ ССЫЛКА/ НЕ РАБОЧАЯ ССЫЛКА ЕСТЬ РЕШЕНИЕ, ПИШИМ СЮДА!