Marques G., Saini J., Dutta M. (eds.) IoT Enabled Computer-Aided Systems for Smart Buildings

Springer, 2023. — 173 p. — (EAI/Springer Innovations in Communication and Computing). — ISBN: 978-3-031-26684-3.This book focuses on the integration of IoT and computer-aided systems for the development of smart buildings. The scope of the book includes but is not restricted to, advanced technologies for monitoring, energy management, smart gardening, protection, safety, assisted living, and intelligent operations. The authors cover the wide aspects of interconnected smart services with convenient interfacing to the end-users. The features of this book include a discussion on various aspects of IoT and computer-aided systems for smart architecture designs and innovative object interconnections. The book also provides highlights on the applications of IoT in the development of intelligent structures for technology-enabled lifestyles. Furthermore, it provides prominent scopes for future inventions in the field of electrical engineering, building system management, and computer-aided advancements. The content of this book is useful to graduate and post-graduate students, researchers, and professionals working on the concept of smart buildings, smart cities, and smart environments.IoT-based devices are connected with sensors and the obtained data may be used for sustainable living and enhanced performance. IoT-based devices may be used effectively for environmental regulation. The artificial intelligence-based technique makes the exchange of data easier. Several IoT systems for IAQ monitoring have been proposed to process the transmission of data and microsensors for the acquisition of data and also enable the transfer of data. Monitoring of O3, CO, NOx, SOX, CO2, VOCs, particulate matter, temperature, and humidity has been made possible by IoT-based sensors which used Raspberry Pi-based sensor modules. Another WSN for IAQ monitoring has been developed using Arduino, XBee modules, and microsensors for storing the monitoring data in real time. The sensor nodes receive data through several sensor nodes through the ZigBee protocol. Another ZigBee WSN system has been proposed to monitor CO2, VOCs, temperature and humidity has been proposed based on the Arduino platform. However, the system does not offer any mobile computing solution. An IAQ monitoring system for AAL based on hybrid IoT/WSN to monitor atmospheric variables has been proposed. It is based on open-source technologies like Arduino and Zigbee.Artificial Intelligence (AI) is one of the oldest fields of computer science that strives to understand the essence of intelligence to compose a new intelligent machine that responds like human intelligence. In recent years, AI techniques and methods have been a key factor in the success of AAL, specifically health monitoring applications. As discussed beforehand, for the AAL to behave intelligently, and to make decisions, there is a necessity for contextual information and intelligence factors. Hence, AI has resulted in a transformation from a conventional system with limited or no intelligence to running systems with the capability of making the right decisions. Since the birth of AI, theories, techniques, and technologies have become more and more mature for handling larger amounts of information. Hence, this results in a growth of AI research that now covers various subfields, including robotics, vision and image recognition, natural language understanding, games, Machine Learning (ML), and expert systems applied in specialized domains (e.g., medical diagnosis, financial analysis, and engineering fault finding). ML is a subfield of AI discipline that is used in AAL health monitoring applications for learning, reasoning, and decision-making tasks.Environmental Data Control in Smart Buildings: Big Data Analysis and Existing IoT Technological Systems.
Need of Technological Interventions for Indoor Air Quality and Risk Assessment Upon Short-Term Exposure: A Futuristic Approach.
Climate-Neutral Districts with Decentralized Energy Production, E-Mobility, and Through the Formation of an Energy Community Exchange of Electricity and Heat.
Zero Water Wastage Smart Garden.
IoT-Based Human Activity Recognition for Smart Living.
Application of Data Mining to Support Facilities Management in Smart Buildings.
Application of Artificial Intelligence in Ambient Assisted Living to Support Elderly People in Smart Homes.