Taxonomic Classification of IoT Smart Home Voice Control

Voice control in the smart home is commonplace, enabling the convenient control of smart home Internet of Things hubs, gateways and devices, along with information seeking dialogues. Cloud-based voice assistants are used to facilitate the interaction, yet privacy concerns surround the cloud analysis of data. To what extent can voice control be performed using purely local computation, to ensure user data remains private? In this paper we present a taxonomy of the voice control technologies present in commercial smart home systems. We first review literature on the topic, and summarise relevant work categorising IoT devices and voice control in the home. The taxonomic classification of these entities is then presented, and we analyse our findings. Following on, we turn to academic efforts in implementing and evaluating voice-controlled smart home set-ups, and we then discuss open-source libraries and devices that are applicable to the design of a privacy-preserving voice assistant for smart homes and the IoT. Towards the end, we consider additional technologies and methods that could support a cloud-free voice assistant, and conclude the work

The Emergence of Artificial Intelligence in the Home: Products, Services, and Broader Developments of Consumer Oriented AI

Current home automation system merges a family\u27s lifestyle with the latest technology & energy management tools to simplify people\u27s lives. It allows users to easily manipulate a variety of home systems, including appliances, security systems, and environmental systems. Setting up a home automation system confuses many consumers. Multiple product lines and platforms make choosing the best system difficult. Basic requirements of setting up a home automation system and the comparison between different platforms are explained. An intelligent home automation system makes intelligent decisions to control a home. This type system might use a weather report to adjust a home\u27s lawn watering schedule, as well as adjust the thermostat for temperature control in the home. Traditional home automation systems require human decision making to control the home system. The future intelligent home will require less human interactions, that can do things automatically after it learns patterns from us. A new generation requires more developed AI to control the smart home automation. Based on the technology we have now, the possible consumer-oriented AI technology is predicted in this paper. When the market is growing rapidly, companies are supposed to have better opportunities to make money. Due to the increasing popularity of home automation systems, the competition is very intense. Companies try the best to take the first mover advantage. Three suggestions are made to help those companies to build their strategies

Smart Home Personal Assistants: A Security and Privacy Review

Smart Home Personal Assistants (SPA) are an emerging innovation that is changing the way in which home users interact with the technology. However, there are a number of elements that expose these systems to various risks: i) the open nature of the voice channel they use, ii) the complexity of their architecture, iii) the AI features they rely on, and iv) their use of a wide-range of underlying technologies. This paper presents an in-depth review of the security and privacy issues in SPA, categorizing the most important attack vectors and their countermeasures. Based on this, we discuss open research challenges that can help steer the community to tackle and address current security and privacy issues in SPA. One of our key findings is that even though the attack surface of SPA is conspicuously broad and there has been a significant amount of recent research efforts in this area, research has so far focused on a small part of the attack surface, particularly on issues related to the interaction between the user and the SPA devices. We also point out that further research is needed to tackle issues related to authorization, speech recognition or profiling, to name a few. To the best of our knowledge, this is the first article to conduct such a comprehensive review and characterization of the security and privacy issues and countermeasures of SPA.Comment: Accepted for publication in ACM Computing Survey

Consumer Contracts, Copyright Licensing, and Control over Data on the Internet of Things

This article presents our interdisciplinary analysis of end-user license agreements and privacy policies from a sample of 22 consumer goods/services connected to the Internet of Things (IoT). We gathered data in the form of legal documents and assessed them from legal and economic perspectives. We developed an original taxonomy of IoT-connected consumer goods/services, classified different business models built around them, and reviewed legal terms and conditions related to their use. Our analysis identifies copyright related restrictions and brings to light issues beyond copyright that merit consideration in the context of a review of copyright law and policy. First, we find that even obtaining legal information on smart products, including software license restrictions and other copyright limitations, is a difficult and time-consuming exercise. Second, our analysis of business models shows interoperability of platforms within an ecosystem of third-party devices and applications, but restrictions that limit interoperability across ecosystems. Third, terms and conditions of consumer use of smart devices in our sample are set up to allow for the collection and transfer of personal data, often sensitive data, in addition to all data collected by the companies from other sources such as social media. Fourth, our study shows that software licensing is now common practice among smart device manufacturers. Based on these findings, we make recommendations to address the issues of accessibility of legal information, data portability, interoperability of systems, and competition. We recommend that governments cooperate with industry, consumer, and public interest groups to: (1) promote labelling standards to help consumers locate and understand the terms on which they acquire and use IoT products and services; (2) support open standards and protocols to facilitate interoperability across platforms; (3) integrate data portability and related issues with ongoing discussions about not only copyright reform but also reforms to privacy laws and other digital rights; and (4) take seriously the relevant recommendations of the Parliamentary Committee for revision to the Copyright Act

Voice-Activated Change: Marketing in the Age of Artificial Intelligence and Virtual Assistants

The Internet of Things promises to make relationships with technology more personal than ever. Voice-controlled virtual or artificial intelligence assistants such as Amazon’s Alexa or Google Assistant execute the commands of their users, providing information, entertainment, utility, and convenience while enabling consumers to bypass the advertising they would typically see on a screen. This “screen-less” communication presents significant challenges for brands used to “pushing” messages to audiences in exchange for the content they seek in hopes of creating preference. It also raises ethical questions about data collection, usage, and privacy. Little is known about the role marketing will play in the increasingly connected, voice-controlled home. This case study explores critical cases to describe the implications, applications, and opportunities for voice-controlled personal assistants in marketing and advertising in the USA

Consumer Adoption of Artificial Intelligence: A Review of Theories and Antecedents

Recently, people are increasingly adopting technologies powered by artificial intelligence (AI) in their everyday lives. Several researchers have investigated this phenomenon using several theoretical perspectives to explain the motivations behind such behaviour. Our paper reviews this body of knowledge to highlight the technologies, theories, and antecedents of AI adoption investigated this far in academic research. By analysing publications found in Harzing's Journal Quality List, this paper identifies 52 publications on user adoption of AI, 198 antecedents, and 36 theoretical perspectives used to explain user adoption of AI. The most widely used theoretical perspectives in this area of research are the technology acceptance model (TAM) and the unified theory of acceptance and use of technology (UTAUT). Meanwhile, perceived usefulness, perceived ease of use, and trust are the most studied antecedents. Finally, we discuss the implications of these findings for future research on AI adoption by consumers

Contextual Factors Affecting Information Sharing Patterns in Technology Mediated Communication

In this thesis, we investigate how and what contextual factors affect user’s information sharing. We build our work on six individual research projects which cover a variety of systems (search engines, social network sites, teleconferencing systems, monitoring technology, and general purpose conversational agents) in a variety of communication scenarios with diverse relationships and dispositions of users. Alongside detailed findings for particular systems and communication scenarios from each individual project, we provide a consolidated analysis of these results across systems and scenarios, which allows us to identify patterns specific for different system types and aspects shared between systems. In particular, we show that depending on the system’s position between a user and an intended information receiving agent – whether communication happens through, around, or directly with the system – the system should have different patterns of operational adaptation to communication context. Specifically, when communication happens through the system, the system needs to gather communication context unavailable to the user and integrate it into information communication; when communication happens around the system, the system should adapt its operations to provide information in the most contextually suitable format; finally, when a user communicates with the system, the role of the system is to “match” this context in communication with the user. We then argue that despite the differences between system types in patterns of required context-based adaptation, there are contextual factors affecting user’s information sharing intent that should be acknowledged across systems. Grounded in our cumulative findings and analysis of related literature, we identify four such high-level contextual factors. We then present these four factors synthesized into an early design framework, which we call SART according to the included factors of space, addressee, reason, and time. Each factor in SART is presented as a continuum defined through a descriptive dichotomy: perceived breadth of communication space (public to private); perceived specificity of an information addressee (defined to undefined); intended reason for information sharing (instrumental to objective); and perceived time of information relevance and life-span (immediate to indefinite)