scholarly journals A conceptual framework for clinicians working with artificial intelligence and health-assistive Smart Homes

2018 ◽  
Vol 26 (1) ◽  
pp. e12267 ◽  
Author(s):  
Gordana Dermody ◽  
Roschelle Fritz
Keyword(s):  
Artificial Intelligence ◽  
Conceptual Framework ◽  
Smart Homes

scholarly journals Human-Centered Artificial Intelligence for Designing Accessible Cultural Heritage

2021 ◽  
Vol 11 (2) ◽  
pp. 870
Author(s):  
Galena Pisoni ◽  
Natalia Díaz-Rodríguez ◽  
Hannie Gijlers ◽  
Linda Tonolli
Keyword(s):  
Artificial Intelligence ◽  
Literature Review ◽  
Cultural Heritage ◽  
Conceptual Framework ◽  
Interaction Design ◽  
Participatory Design ◽  
Future Directions ◽  
Heritage Sites ◽  
Review Analysis

This paper reviews the literature concerning technology used for creating and delivering accessible museum and cultural heritage sites experiences. It highlights the importance of the delivery suited for everyone from different areas of expertise, namely interaction design, pedagogical and participatory design, and it presents how recent and future artificial intelligence (AI) developments can be used for this aim, i.e.,improving and widening online and in situ accessibility. From the literature review analysis, we articulate a conceptual framework that incorporates key elements that constitute museum and cultural heritage online experiences and how these elements are related to each other. Concrete opportunities for future directions empirical research for accessibility of cultural heritage contents are suggested and further discussed.

scholarly journals Responsible Urban Innovation with Local Government Artificial Intelligence (AI): A Conceptual Framework and Research Agenda

2021 ◽  
Vol 7 (1) ◽  
pp. 71
Author(s):  
Tan Yigitcanlar ◽  
Juan M. Corchado ◽  
Rashid Mehmood ◽  
Rita Yi Man Li ◽  
Karen Mossberger ◽  
...  
Keyword(s):  
Artificial Intelligence ◽  
Local Government ◽  
Conceptual Framework ◽  
Research Agenda ◽  
Future Studies ◽  
Expert Team ◽  
Research Questions ◽  
Urban Problems ◽  
Technological Opportunities ◽  
Made In

The urbanization problems we face may be alleviated using innovative digital technology. However, employing these technologies entails the risk of creating new urban problems and/or intensifying the old ones instead of alleviating them. Hence, in a world with immense technological opportunities and at the same time enormous urbanization challenges, it is critical to adopt the principles of responsible urban innovation. These principles assure the delivery of the desired urban outcomes and futures. We contribute to the existing responsible urban innovation discourse by focusing on local government artificial intelligence (AI) systems, providing a literature and practice overview, and a conceptual framework. In this perspective paper, we advocate for the need for balancing the costs, benefits, risks and impacts of developing, adopting, deploying and managing local government AI systems in order to achieve responsible urban innovation. The statements made in this perspective paper are based on a thorough review of the literature, research, developments, trends and applications carefully selected and analyzed by an expert team of investigators. This study provides new insights, develops a conceptual framework and identifies prospective research questions by placing local government AI systems under the microscope through the lens of responsible urban innovation. The presented overview and framework, along with the identified issues and research agenda, offer scholars prospective lines of research and development; where the outcomes of these future studies will help urban policymakers, managers and planners to better understand the crucial role played by local government AI systems in ensuring the achievement of responsible outcomes.

scholarly journals How Companies are Applying AI to the Business Strategy Formulation

2019 ◽  
Vol 5 (8) ◽  
pp. 77
Author(s):  
M S S El Namaki
Keyword(s):  
Artificial Intelligence ◽  
Conceptual Framework ◽  
Business Strategy ◽  
Fundamental Change ◽  
Strategy Formulation ◽  
Strategic Behaviour ◽  
Substantial Progress ◽  
Competitive Behaviour ◽  
Definition Of ◽  
Market Strategies

Computing equipment capable of what one may term partial and quasi-intelligent behaviour, commonly referred to as Artificial Intelligence (AI), is assuming a key role in business. The probability is high that this Artificial Intelligence (AI) will lead to a fundamental change in the process of business strategy formulation as much as the very contents of this strategic behaviour. Product and market strategies and the resultant competitive behaviour will, more likely than not, be the outcome of those artificial intelligence processes and reiterations. A start is made and one can observe substantial progress in this direction. Who has done it and is there a conceptual framework behind this strategic behaviour? This will be the focus of this article The article starts with a brief definition of artificial intelligence and a basic framework of the concept. Seven case studies follow supporting the hypothesis that AI is penetrating the business strategy arena and leading to a fundamental change in the concept as much as the application. Those cases were drawn from different industries, and countries. A conceptual framework is accordingly derived and positioning of those case companies within this conceptual framework is done. The article is based on contemporary frameworks of AI and the cases are drawn from contemporary analysis of strategic behaviour. The conceptual model could provide an instrument for business AI application.

Using artificial intelligence to create value in insurance

2018 ◽  
Vol 36 (6) ◽  
pp. 1145-1168 ◽  
Author(s):  
Mikko Riikkinen ◽  
Hannu Saarijärvi ◽  
Peter Sarlin ◽  
Ilkka Lähteenmäki
Keyword(s):  
Artificial Intelligence ◽  
Conceptual Framework ◽  
Value Creation ◽  
Illustrative Case ◽  
Content Type ◽  
Customer Data ◽  
Case Examples ◽  
Service Logic ◽  
Access To Data ◽  
Convenient Access

Purpose Recent technological and digital developments have opened new avenues for customer data utilization in insurance services. One form of this data transformation is automated chatbots that provide convenient access to data leveraged through a discussion-like interface. The purpose of this paper is to uncover how insurance chatbots support customers’ value creation. Design/methodology/approach Three complementary theoretical perspectives – artificial intelligence, service logic, and reverse use of customer data – are briefly discussed and integrated into a conceptual framework. The suggested framework is further shown through illustrative case examples that characterize different ways of supporting customers’ value creation. Findings Chatbots represent a new type of interaction through which companies can influence customers’ value creation by providing them with additional resources. Based on the proposed conceptual framework and the illustrative case examples, four metaphors are identified that characterize how insurance chatbots can support customers’ value creation. Research limitations/implications The study is conceptual in nature, and the case examples are used for illustrative purposes. No representative data from those users who will eventually determine whether chatbots are of value was used. Practical implications Using the suggested framework, which is aligned with provider service logic, insurance companies can consider what kind of a role they wish to play in customers’ value-creating processes. Originality/value Automated chatbots provide convenient access to data leveraged through a discussion-like interface. This study is among the earliest to address their value-creating potential in insurance.

scholarly journals Review on the Application of Artificial Intelligence in Smart Homes

Smart Cities ◽  
2019 ◽  
Vol 2 (3) ◽  
pp. 402-420 ◽  
Author(s):  
Xiao Guo ◽  
Zhenjiang Shen ◽  
Yajing Zhang ◽  
Teng Wu
Keyword(s):  
Artificial Intelligence ◽  
Smart Home ◽  
Smart Homes ◽  
Product Reviews ◽  
Literature Reviews ◽  
Quality Of Living ◽  
Home Technology ◽  
Smart Home Technology ◽  
The Relationship

Smart home and artificial intelligence technologies are developing rapidly, and various smart home products associated with artificial intelligence (AI) improved the quality of living for occupants. Although some studies discussed the application of artificial intelligence in smart homes, few publications fully considered the integration of literature and products. In this paper, we aim to answer the research questions of “what is the trend of smart home technology and products” and “what is the relationship between literature and products in smart homes with AI”. Literature reviews and product reviews are given to define the functions and roles of artificial intelligence in smart homes. We determined the application status of artificial intelligence in smart home products and how it is utilized in our house so that we could understand how artificial intelligence is used to make smart homes. Furthermore, our results revealed that there is a delay between literature and products, and smart home intelligent interactions will become more and more popular.

scholarly journals Design and Implementation of Cloud Analytics-Assisted Smart Power Meters Considering Advanced Artificial Intelligence as Edge Analytics in Demand-Side Management for Smart Homes

Sensors ◽  
2019 ◽  
Vol 19 (9) ◽  
pp. 2047 ◽  
Author(s):  
Yung-Yao Chen ◽  
Yu-Hsiu Lin ◽  
Chia-Ching Kung ◽  
Ming-Han Chung ◽  
I-Hsuan Yen
Keyword(s):  
Artificial Intelligence ◽  
Data Science ◽  
Modern Society ◽  
Smart Homes ◽  
Demand Side Management ◽  
Demand Side ◽  
Smart Meters ◽  
Smart Power ◽  
Iot Applications ◽  
User Centric

In a smart home linked to a smart grid (SG), demand-side management (DSM) has the potential to reduce electricity costs and carbon/chlorofluorocarbon emissions, which are associated with electricity used in today’s modern society. To meet continuously increasing electrical energy demands requested from downstream sectors in an SG, energy management systems (EMS), developed with paradigms of artificial intelligence (AI) across Internet of things (IoT) and conducted in fields of interest, monitor, manage, and analyze industrial, commercial, and residential electrical appliances efficiently in response to demand response (DR) signals as DSM. Usually, a DSM service provided by utilities for consumers in an SG is based on cloud-centered data science analytics. However, such cloud-centered data science analytics service involved for DSM is mostly far away from on-site IoT end devices, such as DR switches/power meters/smart meters, which is usually unacceptable for latency-sensitive user-centric IoT applications in DSM. This implies that, for instance, IoT end devices deployed on-site for latency-sensitive user-centric IoT applications in DSM should be aware of immediately analytical, interpretable, and real-time actionable data insights processed on and identified by IoT end devices at IoT sources. Therefore, this work designs and implements a smart edge analytics-empowered power meter prototype considering advanced AI in DSM for smart homes. The prototype in this work works in a cloud analytics-assisted electrical EMS architecture, which is designed and implemented as edge analytics in the architecture described and developed toward a next-generation smart sensing infrastructure for smart homes. Two different types of AI deployed on-site on the prototype are conducted for DSM and compared in this work. The experimentation reported in this work shows the architecture described with the prototype in this work is feasible and workable.

Sign in / Sign up

Export Citation Format

Share Document