An Intelligent Smart Plug with Shared Knowledge Capabilities

Gomes, Luís; Sousa, Filipe; Vale, Zita

doi:10.3390/s18113961

Cited by 37 publications

(30 citation statements)

References 19 publications

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“…Internet connections available in most households may enable more flexible programs managed by energy suppliers or third parties [6]. Other solutions are considering the use of enhanced smart plugs which consider user habits and consumption profiles to optimize controllable resources [7].…”

Section: Distributed Load Controlmentioning

confidence: 99%

Privacy-Preserving Overgrid: Secure Data Collection for the Smart Grid

Croce

Giuliano

Tinnirello

et al. 2020

Sensors

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In this paper, we present a privacy-preserving scheme for Overgrid, a fully distributed peer-to-peer (P2P) architecture designed to automatically control and implement distributed Demand Response (DR) schemes in a community of smart buildings with energy generation and storage capabilities. To monitor the power consumption of the buildings, while respecting the privacy of the users, we extend our previous Overgrid algorithms to provide privacy preserving data aggregation (PP-Overgrid). This new technique combines a distributed data aggregation scheme with the Secure Multi-Party Computation paradigm. First, we use the energy profiles of hundreds of buildings, classifying the amount of “flexible” energy consumption, i.e., the quota which could be potentially exploited for DR programs. Second, we consider renewable energy sources and apply the DR scheme to match the flexible consumption with the available energy. Finally, to show the feasibility of our approach, we validate the PP-Overgrid algorithm in simulation for a large network of smart buildings.

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Section: Distributed Load Controlmentioning

confidence: 99%

Privacy-Preserving Overgrid: Secure Data Collection for the Smart Grid

Croce

Giuliano

Tinnirello

et al. 2020

Sensors

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“…This module is responsible to read, write, and control all the hardware resources, from sensors to the actuator(s). The knowledge module integrates all the necessary components that provide knowledge to In the last month of 2018, a new version was proposed in Reference [10] considering the limitations of other proposed smart plugs, such as in References [12,13] where smart plugs were proposed for monitoring, using ZigBee protocol. However, the chosen communication protocol demands a ZigBee hub/gateway to collect the data.…”

Section: Environmental Awareness Smart Plugmentioning

confidence: 99%

“…The gradients are updated according to Nesterov momentum and a threshold of 0.5 is applied to truncate values, as was proposed in Reference [23]. The learning process of EnAPlugs can be seen in detail in Reference [10], where ANN are analyzed and tested according to different inputs, timesteps, and outputs. In this paper, the use of the shared knowledge mechanism over the EnAPlug's learning will be described and tested.…”

Section: Enaplug's Shared Knowledgementioning

confidence: 99%

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A Residential House Comparative Case Study Using Market Available Smart Plugs and EnAPlugs with Shared Knowledge

et al. 2019

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Smart home devices currently available on the market can be used for remote monitoring and control. Energy management systems can take advantage of this and deploy solutions that can be implemented in our homes. One of the big enablers is smart plugs that allow the control of electrical resources while providing a retrofitting solution, hence avoiding the need for replacing the electrical devices. However, current so-called smart plugs lack the ability to understand the environment they are in, or the electrical appliance/resource they are controlling. This paper applies environment awareness smart plugs (EnAPlugs) able to provide enough data for energy management systems or act on its own, via a multi-agent approach. A case study is presented, which shows the application of the proposed approach in a house where 17 EnAPlugs are deployed. Results show the ability to shared knowledge and perform individual resource optimizations. This paper evidences that by integrating artificial intelligence on devices, energy advantages can be observed and used in favor of users, providing comfort and savings.

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“…The home will stop being a static aggregation of resources and will be an active asset that can help and support its users. A smart home may have multiple purposes, such as home automation [1,2], energy management [3][4][5][6], security and safety [7][8][9] or even assisted living [10][11][12]. However, regardless of its purpose, smart homes should provide interoperability to enable the integration of multiple systems-from multiple brands and manufactures.…”

Section: Introductionmentioning

confidence: 99%

IoH: A Platform for the Intelligence of Home with a Context Awareness and Ambient Intelligence Approach

et al. 2019

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This paper presents IoH (Intelligence of Home), a platform developed to test some basic intelligent behaviors in Home context. Internet of Things, ambient intelligence and context awareness approaches motivated the development of IoH. The platform involves six layers, responsible by connectivity, persistency, unification, Internet of Things integration, subsystems integration and user interface. The integrated subsystems involve intelligent systems for light control, television brightness control, desk light control, persons counting and air conditioner control. The IoH platform is then tested for a real building, and results and conclusions are obtained. Different intelligent methods and technologies are used, form the use of a diversity of sensors, actuators, and controllers and processing units to a set of artificial intelligence approaches varying from machine learning and optimization algorithms to the use of sensor fusion and computer vision. The use of IoH day-by-day demonstrated an intelligent performance for the real building occupants.

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An Intelligent Smart Plug with Shared Knowledge Capabilities

Cited by 37 publications

References 19 publications

Privacy-Preserving Overgrid: Secure Data Collection for the Smart Grid

Privacy-Preserving Overgrid: Secure Data Collection for the Smart Grid

A Residential House Comparative Case Study Using Market Available Smart Plugs and EnAPlugs with Shared Knowledge

IoH: A Platform for the Intelligence of Home with a Context Awareness and Ambient Intelligence Approach

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