Smart Home and Artificial Intelligence as Environment for the Implementation of New Technologies

Abstract

The technologies of a smart home and artificial intelligence (AI) are now inextricably linked. The perception and consideration of these technologies as a single system will make it possible to significantly simplify the approach to their study, design and implementation. The introduction of AI in managing the infrastructure of a smart home is a process of irreversible close future at the level with personal assistants and autopilots. It is extremely important to standardize, create and follow the typical models of information gathering and device management in a smart home, which should lead in the future to create a data analysis model and decision making through the software implementation of a specialized AI. AI techniques such as multi-agent systems, neural networks, fuzzy logic will form the basis for the functioning of a smart home in the future. The problems of diversity of data and models and the absence of centralized popular team decisions in this area significantly slow down further development. A big problem is a low percentage of open source data and code in the smart home and the AI when the research results are mostly unpublished and difficult to reproduce and implement independently. The proposed ways of finding solutions to models and standards can significantly accelerate the development of specialized AIs to manage a smart home and create an environment for the emergence of native innovative solutions based on analysis of data from sensors collected by monitoring systems of smart home. Particular attention should be paid to the search for resource savings and the profit from surpluses that will push for the development of these technologies and the transition from a level of prospect to technology exchange and the acquisition of benefits.

Contributions and Risks of Artificial Intelligence (AI) in Building Smarter Cities: Insights from a Systematic Review of the Literature

“…AI paradigms Machine learning [26]; [63]; [67][68][69][70]; Probabilistic methods [70]; [73][74][75]; [77]; [80][81][82]; [87]; [90]; [93,94]; [96][97][98][99][100][101]; [112][113][114]; [134]; [136][137][138] Knowledge-based [26]; [63]; [67][68][69][70][71]; [73]; [77,78]; [82]; [92]; [98]; [100]; [112]; [136]; [139][140][141][142]…”

“…Smarter homes can be developed with AI systems that monitor changes in the environment, adapt to user requirements, and improve energy efficiency [73,92,116]. AI systems could be used to predict future household energy requirements which can help identify inefficiencies, faults, and control future energy use [81].…”

Disruptive Technologies in Smart Cities: A Survey on Current Trends and Challenges

“…Table 3 presents a selection of big data and AI applications in smart city components. Water quality [77,78] Smart lighting [5,79] Planning [70] Healthcare [16,80] Disaster prevention [70] Automating the data management process [81] Transport congestion [9] E-procurement [46] Entrepreneurial opportunities [48] Crowd monitoring [73,74] Air quality prediction [82] Complex statistical analyses [81] Smart parking [83] Public safety [73,74] Social comfort [57] Building management [84] Efficient energy [5,84,85] Perform repetitive tasks [9] Vehicle auto-diagnosis [9] Smart home [86] Waste management [50,72] According to Guevara et al [38], big data and IoT due to 5G technologies will gather more useful information for citizens. The automotive industry is an example of an industry with major benefits brought by the evolution of AI and IoT.…”

A Collaborative Framework With Artificial Intelligence for Long-Term Care

“…These agencies may provide information on the availability of caretakers in advance to provide a ''window period'' if they are not ready to receive a patient or a task related to them. However, few studies combine artificial intelligence technologies and long-term care together with the integration of suitability and older people [22]. In addition, existing methods retain some issues of insufficient suitability after applying artificial intelligence applications into the collaborative platform [23].…”