Big Data and Personalisation for Non-Intrusive Smart Home Automation

Abstract

With the advent of the Internet of Things (IoT), many different smart home technologies are commercially available. However, the adoption of such technologies is slow as many of them are not cost-effective and focus on specific functions such as energy efficiency. Recently, IoT devices and sensors have been designed to enhance the quality of personal life by having the capability to generate continuous data streams that can be used to monitor and make inferences by the user. While smart home devices connect to the home Wi-Fi network, there are still compatibility issues between devices from different manufacturers. Smart devices get even smarter when they can communicate with and control each other. The information collected by one device can be shared with others for achieving an enhanced automation of their operations. This paper proposes a non-intrusive approach of integrating and collecting data from open standard IoT devices for personalised smart home automation using big data analytics and machine learning. We demonstrate the implementation of our proposed novel technology instantiation approach for achieving non-intrusive IoT based big data analytics with a use case of a smart home environment. We employ open-source frameworks such as Apache Spark, Apache NiFi and FB-Prophet along with popular vendor tech-stacks such as Azure and DataBricks.

Bringing Smart Home Technology to Peer-to-Peer Accommodation: Exploring the Drivers of Intention to Stay in Smart Accommodation

“…smart cameras) does not diminish the utility of technology during the stay. This finding contradicts the literature discussing the risk of privacy intrusion and uncertainty concerns when using smart home systems (Asaithambi et al, 2021 ; Jung et al, 2021 ). Considering the preferences of respondents, scoring smart cameras as one of the least preferred devices, it is likely that renters would not feel comfortable using cameras in accommodation.…”

“…Hence, the greater degree of the customisation of services provides a higher level of control over experience in smart accommodation compared to a traditional setting. On the other hand, the embeddedness of smart sensors in a private environment entails concerns related to potential surveillance and, in turn, the third-party use of personal data (Asaithambi et al, 2021 ). Perceived surveillance can reduce the functional value of smart accommodation.…”

Creating Smart Cities: A Review for Holistic Approach

“…Some studies have explored cross-domain areas such as between technologies and management of people requirements [35,36]. However, most studies published on smart cities remain to be 'thing-based' rather than people-based, where the emphasis of the study predominantly revolves more around infrastructure, engineering, Internet, data, technology, etc., than about the people who live in it [11,12] as claimed in the recent studies.…”

“…Insights obtained from the information collected are utilised to manage multiple resources, assets and services more efficiently, thereby improving the operations enabling corporate sustainability [2] (considering sustainability's four pillars affecting environmental, social, human and economic spheres) and service quality across the entire city [3]. Some recent reviews carried out in this context [4] covering the technical standards [5], future of smart cities [6], technologies and sustainability [7,8], Big Data architecture [9], self-driving vehicles [10] smart home automation [11], facial recognition [12] and applications of artificial intelligence and machine learning [13] to name a very few of the studies. The objective of this review is to reorient the perception of 'smart city' from the idea of machines and things, and towards people, which should be at the heart of these things.…”

Analysis of Smart Home Systems in the Context of the Internet of Things in Terms of Consumer Experience

“…These platforms are energy-efficient, connect heterogeneous devices and protocols, facilitate remote control and operation, and support third-party application development (Khoa et al, 2020). Smart homes are defined by (Lutolf, 1992 andAldrich, 2003) as economical, safe, fun, and comfortable houses equipped with information technology, by (Gross, 1998;Ricquebourg et al, 2007;by Ricquebourg et al, 2007;Sripan et al, 2012;Balta-Özkan et al, 2014;Hargreaves and Wilson, 2017;Georgiev and Schlögl, 2018;Javed et al, 2018;Marikyan et al, 2019;Hall et al, 2020;Asaithambi et al, 2021;Yang and Han, 2021;Qashlan et al, 2021;) as homes that connect sensors, household appliances, and devices that can be monitored, accessed or controlled remotely, equipped with a communication network that can be used and provides services that meet the needs of their residents, by (Robles and Kim, 2010;Kadam et al, 2015) as an integration of technology and services through the home network for a better quality of life and by (Dewsbury et al, 2001) as "a house in which the scope of a standard house goes beyond brick and mortar and is equipped with technological devices. "…”