Internet of Things and artificial intelligence enable energy efficiency

Tomazzoli, Claudio; Scannapieco, Simone; Cristani, Matteo

doi:10.1007/s12652-020-02151-3

Cited by 28 publications

(8 citation statements)

References 58 publications

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“…Stavropoulos et al (2015), a new agent with a GUI was introduced allowing the management of the rule engine through a user-friendly interface. A similar approach was implemented also by Cristani et al (2014); Tomazzoli, Scannapieco, and Cristani (2020) with three main menu choices, allowing manual activation of physical devices, setting of rules, actions and scenarios and also measurement of energy consumption and displaying along with real-time and stored data. Alsalemi et al (2019b) implemented (EM) 3 , a system with an end-user web application contained on-line daily consumption monitoring, displaying also indoor and outdoor levels of temperature and humidity, providing at the same time recommendations about energy efficiency.…”

Section: Monitoring and Management Applicationsmentioning

confidence: 99%

Intelligent Energy Management Systems -- A Review

Mischos¹,

Eleanna²,

Vrakas³

2022

Preprint

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Climate change has become a major problem for humanity in the last two decades. One of the reasons that caused it, is our daily energy waste. People consume electricity in order to use home/work appliances and devices and also reach certain levels of comfort while working or being at home. However, even though the environmental impact of this behavior is not immediately observed, it leads to increased CO2 emissions coming from energy generation from power plants. Confronting such a problem efficiently will affect both the environment and our society. Monitoring energy consumption in real-time, changing energy wastage behavior of occupants and using automations with incorporated energy savings scenarios, are ways to decrease global energy footprint. In this review, we study intelligent systems for energy management in residential, commercial and educational buildings, classifying them in two major categories depending on whether they provide direct or indirect control. The article also discusses what the strengths and weaknesses are, which optimization techniques do they use and finally, provide insights about how these systems can be improved in the future.

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Section: Monitoring and Management Applicationsmentioning

confidence: 99%

Intelligent Energy Management Systems -- A Review

Mischos¹,

Eleanna²,

Vrakas³

2022

Preprint

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“…This architecture leads to the necessity of setting a local system for interconnecting IoT sensors and actuators over a geographical network (such as the Internet), executing sort of local computation and buffering data in case of connection blackout, using the known "ubiquitous and pervasive computing" [46] techniques to deal with the computational problems of centralized intelligence.…”

Section: Artificial Intelligencementioning

confidence: 99%

“…Considering a single location, using ML techniques and rule-based methods such as association rule learning, it is possible to deduce which device is active at a certain time for each selected location [46].…”

Section: Obtain Data Train and Test Modelsmentioning

confidence: 99%

Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence

et al. 2021

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The research explores the potential of digital-twin-based methods and approaches aimed at achieving an intelligent optimization and automation system for energy management of a residential district through the use of three-dimensional data model integrated with Internet of Things, artificial intelligence and machine learning. The case study is focused on Rinascimento III in Rome, an area consisting of 16 eight-floor buildings with 216 apartment units powered by 70% of self-renewable energy. The combined use of integrated dynamic analysis algorithms has allowed the evaluation of different scenarios of energy efficiency intervention aimed at achieving a virtuous energy management of the complex, keeping the actual internal comfort and climate conditions. Meanwhile, the objective is also to plan and deploy a cost-effective IT (information technology) infrastructure able to provide reliable data using edge-computing paradigm. Therefore, the developed methodology led to the evaluation of the effectiveness and efficiency of integrative systems for renewable energy production from solar energy necessary to raise the threshold of self-produced energy, meeting the nZEB (near zero energy buildings) requirements.

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“…Saving energy in buildings is connected to measuring and controlling the IoT devices in an efficient way that takes into account each power level, as well as the interconnections among smart home devices [21].…”

Section: Ease Of Use and Accessibility Of Iot Products Aiming At Energy Savingmentioning

confidence: 99%

The Challenge for Energy Saving in Smart Homes: Exploring the Interest for IoT Devices Acquisition in Romania

Micu

Geru

et al. 2021

Energies

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The Internet of Things (IoT) is a shift towards a digitally enriched environment that connects smart objects and users, aiming to provide merchants with innovative ways to communicate with customers. Therefore, the aim of this research was to identify the Romanian consumer′s openness to technological autonomy and the degree of acceptance of IoT services and technologies to address the green deal principle of low energy consumption. This article investigated the factors that influence the decision to buy smart IoT devices and customers′ perception regarding the security of the data generated in this process. Based on the Technology Acceptance Model (TAM), this research proposed an alternative model consisting of 18 items measured on a Likert scale in order to identify the factors that contribute to the perceived value of the consumer and the behavioral precursors impacting the decision to purchase IoT products. More and more products have built-in sensors and through the Internet connection generate valuable data from a managerial point of view in relation to the customer. Although these data are expected to be of great value to companies, the way they are used is not always transparent and can affect the purchasing decisions and the behavior of IoT products′ customers. The findings of this paper aimed to better promote Smart Home IoT technologies and devices among Romanian people, making possible the control of consumption and the generation of energy savings.

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Internet of Things and artificial intelligence enable energy efficiency

Cited by 28 publications

References 58 publications

Intelligent Energy Management Systems -- A Review

Intelligent Energy Management Systems -- A Review

Cyber-Physical Systems Improving Building Energy Management: Digital Twin and Artificial Intelligence

The Challenge for Energy Saving in Smart Homes: Exploring the Interest for IoT Devices Acquisition in Romania

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