Book Image

Internet of Things for Smart Buildings

By : Harry G. Smeenk
5 (1)
Book Image

Internet of Things for Smart Buildings

5 (1)
By: Harry G. Smeenk

Overview of this book

Imagine working in a building with smart features and tenant applications that allow you to monitor, manage, and control every aspect of your user experience. Internet of Things for Smart Buildings is a comprehensive guide that will help you achieve that with smart building architecture, ecosystems, technologies, and key components that create a smart building. In this book, you’ll start by examining all the building systems and applications that can be automated with IoT devices. You’ll learn about different apps to improve efficiency, reduce consumption, and improve occupant satisfaction. You’ll explore IoT sensors, devices, computing platforms, analytics software, user interfaces, and connectivity options, along with common challenges you might encounter while developing the architecture. You’ll also discover how to piece different components together to develop smart buildings with the help of use cases and examples and get to grips with the various IoT stacks. After finding out where to start developing the requirements for your project, you’ll uncover a recommended methodology to understand your current building systems and a process for determining what needs to be modified, along with new technology requirements. By the end of the book, you’ll be able to design and build your own smart building initiative, turning your city into a smart city with one building at a time.
Table of Contents (22 chapters)
1
Part 1: Applications for Smart Buildings
7
Part 2: Smart Building Architecture
11
Part 3: Building Your Smart Building Stack
15
Part 4: Building Sustainability for Contribution to Smart Cities

Intelligent learning

Throughout this book, we have referenced AI, ML, and deep learning and their impact on smart buildings. In this section, we will discuss each of these in more detail and their expected contribution from smart buildings to unified buildings.

Figure 15.5 – Intelligent learning

Figure 15.5 – Intelligent learning

  • AI: AI is comprised of neural networks, deep learning, and ML, which process data to make predictions and decisions. AI can be loosely defined as machines thinking like humans.
  • Artificial neural networks (ANNs): An ANN, more commonly referred to as a neural network, is modeled after the brain’s biological neurons. Here, the neurons are called nodes, and these nodes are clustered together in layers and operate in parallel. When a node receives a computerized numerical signal, it will process it, and then it signals the other neurons connected to it. This neural reinforcement creates improved recognition of patterns and expertise and enhances...