Smart Homes and Sustainable Cities: The Design of a Low-Cost Solution for Comprehensive Home Automation

The challenge for smart cities is to connect as many of its inhabitants to technology enabling solutions that improve their lives. Smart homes provide all users a means of interacting and impacting their environment. In developing economies this proves challenging and these challenges are daunting and overwhelming since system costs are always a foreboding factor. The chapter addresses these challenges by providing a low-cost solution for a home energy saving measure. It introduces an overview of enabling technologies for a smart home by considering energy management, energy saving, load management and monitoring and control of living spaces. By leveraging the application of the Internet of Things (IoT) and load management strategies, the realisation of a smart home is made possible. This chapter presents a broad overview of the design and development of a web-enabled smart home solution. Web development and control systems together form the backbone of automation for modern home automation technologies such as the Internet of Things and embedded systems. The developed web-enabled home automation incorporates elements of web developed software application and digital control systems. The web-enabled interface energy saving measure is a networked system that uses web-enabled applications for enabling energy efficiency by incorporating load management, remote power consumption, monitoring and control

Tabulator Redux: writing Into the Semantic Web

A first category of Semantic Web browsers were designed to present a given dataset (an RDF graph) for perusal, in various forms. These include mSpace, Exhibit, and to a certain extent Haystack. A second category tackled mechanisms and display issues around linked data gathered on the fly. These include Tabulator, Oink, Disco, Open Link Software's Data Browser, and Object Browser. The challenge of once that data is gathered, how might it be edited, extended and annotated has so far been left largely unaddressed. This is not surprising: there are a number of steep challenges for determining how to support editing information in the open web of linked data. These include the representation of both the web of documents and the web of things, and the relationships between them; ensuring the user is aware of and has control over the social context such as licensing and privacy of data being entered, and, on a web in which anyone can say anything about anything, helping the user intuitively select the things which they actually wish to see in a given situation. There is also the view update problem: the difficulty of reflecting user edits back through functions used to map web data to a screen presentation. In the latest version of the Tabulator project, described in this paper we have focused on providing the write side of the readable/writable web. Our approach has been to allow modification and addition of information naturally within the browsing interface, and to relay changes to the server triple by triple for least possible brittleness (there is no explicit 'save' operation). Challenges which remain include the propagation of changes by collaborators back to the interface to create a shared editing system. To support writing across (semantic) Web resources, our work has contributed several technologies, including a HTTP/SPARQL/Update-based protocol between an editor (or other system) and incrementally editable resources stored in an open source, world-writable 'data wiki'. This begins enabling the writable Semantic Web

When Things Matter: A Data-Centric View of the Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. While IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy, and continuous. This article surveys the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed

Integration of Blockchain and Digital Twins in the Smart Built Environment Adopting Disruptive Technologies—A Systematic Review

The integration of blockchain and digital twins (DT) for better building-lifecycle data management has recently received much attention from researchers in the field. In this respect, the adoption of enabling technologies such as artificial intelligence (AI) and machine learning (ML), the In-ternet of Things (IoT), cloud and edge computing, Big Data analytics, etc., has also been investigated in an abundance of studies. The present review inspects the recent studies to shed light on the foremost among those enabling technologies and their scope, challenges, and integration potential. To this end, 86 scientific papers, recognized and retrieved from the Scopus and Web of Science databases , were reviewed and a thorough bibliometric analysis was performed on them. The obtained results demonstrate the nascency of the research in this field and the necessity of further implementation of practical methods to discover and prove the real potential of these technologies and their fusion. It was also found that the integration of these technologies can be beneficial for addressing the implementation challenges they face individually. In the end, an abstract descriptive model is presented to provide a better understanding of how the technologies can become integrated into a unified system for smartening the built environment

When things matter: A survey on data-centric Internet of Things

With the recent advances in radio-frequency identification (RFID), low-cost wireless sensor devices, and Web technologies, the Internet of Things (IoT) approach has gained momentum in connecting everyday objects to the Internet and facilitating machine-to-human and machine-to-machine communication with the physical world. IoT offers the capability to connect and integrate both digital and physical entities, enabling a whole new class of applications and services, but several significant challenges need to be addressed before these applications and services can be fully realized. A fundamental challenge centers around managing IoT data, typically produced in dynamic and volatile environments, which is not only extremely large in scale and volume, but also noisy and continuous. This paper reviews the main techniques and state-of-the-art research efforts in IoT from data-centric perspectives, including data stream processing, data storage models, complex event processing, and searching in IoT. Open research issues for IoT data management are also discussed