SMART HOME ENERGY SAVING WITH BIG DATA AND MACHINE LEARNING

In response to escalating energy consumption, particularly within the housing sector, a global imperative to reduce energy usage has emerged, propelling the concept of "smart houses" to the forefront of innovation. This paradigm shift owes its genesis to the convergence of advancements in energy conversion, communication networks, and information technology, catalyzing the emergence of the Internet of Things (IoT). The IoT facilitates seamless connectivity of devices via the World Wide Web, enabling remote management, monitoring, and detection capabilities. Capitalizing on this technological synergy, the integration of IoT, big data, and machine learning with home automation systems holds immense promise for enhancing energy efficiency. This paper introduces HEMS-IoT, a groundbreaking energy control system for intelligent homes, underpinned by big data analytics and machine learning algorithms, prioritizing security, convenience, and energy conservation. Leveraging J48 neural network technology and the Weka API, the study illuminates user behaviors and energy consumption patterns, enabling household classification based on energy usage profiles. Moreover, to ensure user comfort and safety, RuleML and Apache Mahout are deployed to customize energy-saving recommendations tailored to individual preferences. By presenting a practical demonstration of smart home monitoring, this paper validates the effectiveness of the proposed approach in enhancing security, comfort, and energy conservation. This pioneering research not only showcases the transformative potential of IoT-driven energy management systems but also sets the stage for a sustainable and interconnected future

A Human-Machine Interface Based on Eye Tracking for Controlling and Monitoring a Smart Home Using the Internet of Things

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Representação da informação incerta por meio de ontologias: um framework para smart homes

Dissertação (mestrado) - Universidade Federal de Santa Catarina, Centro de Ciências da Educação, Programa de Pós-Graduação em Ciência da Informação, Florianópolis, 2019.Nas smart homes e outros cenários da Internet das Coisas (IoT), muitas vezes, as informações coletadas estão sujeitas a interferências externas. Além disso, pode ser necessário representar situações nas quais não é possível se obter informações completas ou precisas sobre determinado fenômeno, gerando a necessidade de se lidar com a informação incerta. As ontologias apresentam um formato amplamente utilizado para a representação das informações coletadas nas smart homes. Sendo assim, atualmente existem várias abordagens não padronizadas na literatura baseadas em ontologias para a representação da informação incerta, ou ontologias incertas . Diante desse contexto, o objetivo deste trabalho é propor um framework para ser utilizado como ferramenta de referência no processo de seleção de ontologias incertas para cenários de smart homes. Para isso, foram identificadas ontologias incertas para smart homes por meio de uma Revisão Sistemática da Literatura (RSL) e foram realizadas pesquisas nos anais do International Workshop on Uncertainty Reasoning for the Semantic Web (URSW). O framework proposto é composto por dois artefatos gerados a partir de informações extraídas das ontologias incertas identificadas: a) questionário para auxiliar na identificação das necessidades de representação da informação incerta; e b) quadro de referência para ser consultado durante a seleção de uma ontologia incerta de acordo com as necessidades de representação da informação incerta. Ao todo, foram identificados 16 trabalhos que propõem ontologias incertas. Com base nestes trabalhos, elaborou-se o questionário com seis questões e diferentes opções de respostas que remetem as ontologias incertas. O quadro de referência foi elaborado contendo os 16 trabalhos identificados e as características das ontologias incertas propostas por cada trabalho. O framework foi aplicado em nove cenários de smart homes que utilizam ontologias, mas não representam a informação incerta, de modo a exemplificar o papel do framework como ferramenta de referência. Como resultado de sua aplicação, para cada cenário, exceto um, identificou-se uma ou mais opções de ontologias incertas. Isto indica que as ontologias incertas disponíveis cobrem grande parte das necessidades de representação atualmente, mas não completamente. Espera-se que o framework proposto possa ser utilizado como referência para facilitar o acesso e uso das ontologias incertas pelos profissionais interessados na construção de ontologias. Finalmente, espera-se gerar oportunidades para que sejam desenvolvidas aplicações que elevem a qualidade e capacidade dos cenários de smart homes tendo em vista principalmente as necessidades e bem-estar das pessoas.Abstract : In smart homes and other Internet of Things (IoT) scenarios, often information collected is subject to external interference. Moreover, it may be necessary to represent situations in which it is not possible to obtain complete or accurate information about a specific phenomenon, causing the need to deal with uncertain information. Ontologies provides a widespread format for representing information collected in smart homes. This way, nowadays there are many non-standard ontology-based approaches in literature focused in the task of uncertain information representation, or \"uncertain ontologies\". Given this context, the objective of this work is to propose a framework to be used as a reference tool in the process of selecting uncertain ontologies for smart home scenarios. For this purpose, uncertain ontologies for smart homes and other IoT scenarios are identified by means of a Systematic Review of Literature (RSL) and by research in proceedings from International Workshop on Uncertainty Reasoning for the Semantic Web (URSW). The proposed framework is composed by two artifacts generated from information extracted from identified uncertain ontologies: a) a survey to assist in identifying the needs for representing uncertain information; and b) a reference table which can be used for selection of uncertain ontologies according to the representation needs. Altogether, 16 uncertain ontologies proposals have been identified. Based on these proposals, the questionnaire was elaborated with six questions and different options of answers referring to uncertain ontologies. The reference table was built containing the 16 ontologies proposals and its specific features. The framework was applied in nine scenarios of smart homes which use ontologies, but do not represent the uncertain information, in order to exemplify the role of the framework as a reference tool. As a result of its application one or more uncertain ontologies options were identified for most of the work. This indicates that the available uncertain ontologies cover most of the representation needs currently, but not all. It is expected that the proposed framework will be used as a reference to ease the access and use of uncertain ontologies by professionals interested in the creation of ontologies. Finally, it is expected to generate opportunities to develop applications which raise the quality and capacity of smart home scenarios especially in view of the needs and well-being of people

Access management for digital twins in the built environment

Recent technological advances in the built environment have sought to create smart cities by coupling information models such as BIM with Cyber-Physical Systems (CPSs). BIM models are now widely used together with IoT-based systems and embrace smart technologies that provide communication layer compatibility. Digital twins are expected to open new opportunities for cyber-physical systems in the future through monitoring and simulation. Security, on the other hand, is rarely properly considered in this fast-evolving industry. However, while they provide various advantages, according to the literature, they also present a number of concerns, the most serious of which is security. Attempting to integrate access management into digital twins that will be used in built-environment applications presents significant obstacles. Furthermore, this is an issue that has received too little attention. As a result, digital twins that can safeguard and identify real twins are in demand. This research focuses on how to enhance the access management frameworks for digital twins in the built environment, paying particular attention to access control, data confidentiality, data integrity, and Single Sign-On (SSO). As a result, this thesis defines an access management framework for digital twins in the built environment that is supported by a requirement specification of access management ontology This study engages with built environment experts to consider their role as stakeholders and identifies their main concerns, gauges their assessments of current technologies and utilities, and stimulates public awareness of built environment applications’ development goals. According to these findings, there is still a need for a suitable and safe access management paradigm for digital twins. Those in charge of overseeing smart building investments and the use of BIM in asset design and management must be aware of the latest access management threats and take steps to prevent any risk to the shared data environment. Therefore, this study has developed a semantically defined access management framework for the built environment through an ontological modelling method which formally represents domain information in the creation stage. This ontology solves the issues identified by previous research and industry surveys by explicitly modelling the relationships in an access management context between physical built environment assets, IoT devices, cyber-physical systems, current built environment services, existing security standards, digital twin and BIM datasets, as well as user interfaces and the actors who use them The fundamental novelty of this framework is that while previous work has focused on IoT platforms that integrate with BIM, none of these platforms allow seamless integration with BIM models. The need to be able to operate secure servers appears to have been disregarded in efforts to solve access management problems. The access management framework is validated using a case study from Cardiff University achieved validating the semantic representation against the competency questions and on data drawn from existing case studies developed on university buildings. The validation has shown that the final access management framework semantic representation satisfies the defined requirements and is suitable for application in various built environment use cases. Furthermore, its functionality is tested in the specified case study, as is its compatibility with the necessary built-environment principles such as SSO. The key contributions of this study are that it (a) finds the current IoT and CPS security systems to address the access management threats facing digital twins in the context of smart buildings and districts; (b) finds built environment experts to consider their role as a stakeholder and to identify their main concerns; and (c) enhances the access management framework for digital twins in the built environment. Finally, numerous important recommendations are suggested for future research to help overcome the current study’s limitations. These recommendations are designed to stimulate future research in the areas of built environment access management, digital twins, and cyber physical system