Efficient Energy Management for the Internet of Things in Smart Cities

Ejaz, Waleed; Naeem, Muhammad; Shahid, Adnan; Anpalagan, Alagan; Jo, Minho

doi:10.1109/mcom.2017.1600218cm

Cited by 414 publications

(195 citation statements)

References 13 publications

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“…IoT: Providing energyefficient optimization and scheduling of IoT-based smart cities (Ejaz, Naeem, Shahid, Anpalagan, & Jo, 2017). IoA: Smart recommendation system to perform the decisions regarding energy devices (when, why, and how to connect) according to the contextual background based on cognitive entities.…”

Section: Energy Maintenancementioning

confidence: 99%

Towards the Internet of Agents: An Analysis of the Internet of Things from the Intelligence and Autonomy Perspective

et al. 2018

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Recently, the scientific community has demonstrated a special interest in the process related to the integration of the agent-oriented technology with Internet of Things (IoT) platforms. Then, it arises a novel approach named Internet of Agents (IoA) as an alternative to add an intelligence and autonomy component for IoT devices and networks. This paper presents an analysis of the main benefits derived from the use of the IoA approach, based on a practical point of view regarding the necessities that humans demand in their daily life and work, which can be solved by IoT networks modeled as IoA infrastructures. It has been presented 24 study cases of the IoA approach at different domains --smart industry, smart city and smart health wellbeing--in order to define the scope of these proposals in terms of intelligence and autonomy in contrast to their corresponding generic IoT applications. Keywords:Internet of Things, agents, smart industry, smart city, smart health wellbeing. RESUMENEn los últimos años, la comunidad científica ha mostrado un interés especial en torno al proceso de integración de la tecnología orientada a agentes sobre plataformas de Internet de las Cosas (IoT, por sus siglas en inglés). Surge así, un nuevo enfoque denominado Internet de los Agentes (IoA, por sus siglas en inglés) como una alternativa para añadir un componente de inteligencia y autonomía sobre los dispositivos y redes de IoT. El presente trabajo muestra un análisis de los principales beneficios derivados del uso del enfoque del IoA, visto desde las actuales necesidades que el ser humano demanda en su trabajo y vida cotidiana, las cuales pueden ser resueltas por redes de IoT modeladas como infraestructuras de IoA. Se plantea un total de 24 casos prácticos de aplicaciones de IoA en diferentes dominios --industria, ciudad, y salud y bienestar inteligente--a fin de determinar el alcance de dichas aplicaciones en términos de inteligencia y autonomía respecto a sus correspondientes aplicaciones genéricas de IoT.Palabras clave: Internet de las Cosas, agentes, industria inteligente, ciudad inteligente, salud y bienestar inteligente.

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Section: Energy Maintenancementioning

confidence: 99%

Towards the Internet of Agents: An Analysis of the Internet of Things from the Intelligence and Autonomy Perspective

et al. 2018

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“…In this context, the development of optimization methods that use nature‐inspired metaheuristic algorithms such as genetic algorithms for hybrid energy demand forecasting approaches represents an interesting future research direction for Evolutionary Computation researchers . Assuming the potentially wide applicability of the time series forecasting method and the ML methods for Big data analytics that are behind the recommendations generated by IntelliHome, the results of this study may be reasonably extrapolated to the domains of smart cities and smart grids, which increases its potential impact and interestingness among researchers from the corresponding research areas …”

Section: Introductionmentioning

confidence: 96%

“…[22][23][24] Assuming the potentially wide applicability of the time series forecasting method and the ML methods for Big data analytics that are behind the recommendations generated by IntelliHome, the results of this study may be reasonably extrapolated to the domains of smart cities and smart grids, which increases its potential impact and interestingness among researchers from the corresponding research areas. [25][26][27][28] The remainder of this paper is structured as follows: Section 2 describes the relevant literature on energy management systems for smart homes. Then, Section 3 describes the functional architecture of IntelliHome, highlighting those components aiming to optimize electrical energy consumption.…”

Section: Introductionmentioning

confidence: 99%

IntelliHome: An internet of things‐based system for electrical energy saving in smart home environment

Paredes-Valverde

Alor-Hernández

Alcaráz³

et al. 2019

Computational Intelligence

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Despite there has been an increasing energy price due to factors such as supply, demand, government regulation, among others, users do not like to spend their time to analyze their power consumption and establish actions to save money. Hence, there is a need for smart solutions that help users to save energy at home in an easy way. The smart home concept is attracting the attention of both academia and industry to address this need. Nowadays, high volumes of data are available in the smart home context, facilitated by the growth of internet of things (IoT)‐based devices and advanced sensing infrastructure. Therefore, it is necessary to automatically extract useful knowledge from this information to cost‐effective use of energy at home. In this sense, this work presents IntelliHome, a smart‐home system that aims to reduce electrical energy consumption at home. To this end, IntelliHome uses big data analytics technologies and Machine Learning and statistical techniques to provide users with a meaningful perspective of their electricity consumption habits aiming to actively involve them in the energy‐saving process through real‐time information and energy‐saving recommendations. This work also discusses a case study and an evaluation aligned with the objectives of this work. The obtained results verify the effectiveness of the proposed system regarding electrical energy saving.

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“…On the other hand, the drastic increase in the internet of things (IoT) devices results in a significant enhancement in the energy demand. In this regard, smart solutions for the wireless environment are inevitable due to the increase of the wireless communication demands and their enormous energy utilizations [2]. Smart cities are the appropriate solutions to deal with the mentioned need since they are capable of providing energy efficiency in the networks.…”

Section: Introductionmentioning

confidence: 99%

Downlink user association and uplink scheduling for energy harvesting users in software-defined mobile networks

Yeganeh

Rostampoor

2018

Physical Communication

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In this paper we consider a heterogeneous network which consists of a macro base station and some pico base stations utilizing massive MIMO and MIMO techniques, respectively. A central software-defined mobile network (SDMN) controller is adopted in order to provide user association and energy scheduling. The users are considered battery limited and are capable of simultaneous wireless information and power transfer (SWIPT) in order to harvest energy and address the energy shortage issue. These users harvest energy from the received signals in the downlink and consume it via their uplink communications. This paper deals with the downlink user association by jointly optimizing the overall sum-rate of the network and the harvested energy by introducing an appropriate utility function. In this regard, the optimum user association and power splitting factor for each user are calculated via the downlink optimization stage. Then, the process of uplink scheduling is defined as choosing the best users in each time epoch to transfer data as well as optimizing their transmit power by solving Lyapunov drift-plus-penalty function. Simulation results are provided in order to confirm the optimality of the proposed algorithm in comparison with the previous user association and uplink scheduling approaches in terms of providing fairness and battery management among users.

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Efficient Energy Management for the Internet of Things in Smart Cities

Cited by 414 publications

References 13 publications

Towards the Internet of Agents: An Analysis of the Internet of Things from the Intelligence and Autonomy Perspective

Towards the Internet of Agents: An Analysis of the Internet of Things from the Intelligence and Autonomy Perspective

IntelliHome: An internet of things‐based system for electrical energy saving in smart home environment

Downlink user association and uplink scheduling for energy harvesting users in software-defined mobile networks

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