In this work, the main objective is oriented towards the development of a completed system of saving energy at a home in south Algeria. The proposed previously solution (OSEIM) is an intelligent solution based on domain ontology for the electrical energy management in the home; these are designed, built, and operated with increasingly complex technologies. However, the ontology used in this work brings

The energy consumption of large Information and Communications Technology structures such as data and computation centers along with the corresponding carbon footprint are on the rise. Green computing has become an indispensable solution to face the resulting economical and environmental challenges. Powering these centers with renewable energy sources is however a challenge since these sources cannot

Mobile device usage is increasing in daily life and almost everybody carries one. The devices now have more processing power, battery, memory, and a big display. However, they have limited battery lives. Software developers should focus on optimizing applications and systems by using resources and sensors efficiently to reduce their energy consumption. Developers lack the knowledge to enhance the energy

This paper presents a crowdsensing platform for real-time monitoring and analysis of noise pollution in smart cities. The aim is to develop a comprehensive methodology and scalable infrastructure for measuring noise using mobile crowdsensing, storing and analysis of gathered data. The developed system consists of: 1) a mobile application for participatory and opportunistic crowdsensing of noise data

Vehicular communication plays a dominant role in providing better safety and security with high rate of data communication in next generation networking infrastructure, and one of the prominent areas for research as well. As the growth in vehicular communication has seen a prominent improvement in vehicle to vehicle communication, vehicle to infrastructure and vehicular to pedestrian communication

Energy conservation is of increasing importance in contemporary society. A large fraction of energy end-use can be attributed to space conditioning. Therefore, intelligent control systems were devised and commercialised in the form of smart thermostats. Hereto, the availability of occupancy information is essential such that heating and/or cooling schedules can be tailored to user needs. This way energy

With the introduction and popularization of the concept of smart agriculture, smart agriculture has become the future direction of agricultural development, and how to promote the construction and development of smart agriculture has become the focus of research. At present, many achievements have been made in the systematic framework of smart agriculture, but the measures to promote the construction

The core of green technological innovation is to protect the ecology. The innovative introduction of ecological concepts into the existing ecosystem can ensure the sustainable development and progress of society. This paper mainly studies the path analysis of green technology innovation based on blockchain algorithm. Aiming at the high latency and low efficiency of pbft algorithm in green technology

Agriculture is one of the foremost and the minimum salaried employment in India. Data mining be able to fetch an explosion in the agriculture field by altering the profits scenario through growing the optimum crop with crop yield prediction, which is a difficult task because of the climatic factors, soil fertility, nutrients and so on. Precise crop forecast requires fundamental understanding of the

The energy hole problem is a major concern in the wireless sensor network (WSN) given the uneven energy depletion of the power-constrained sensor nodes. Recently, several studies have incorporated a mobile data collector (MDC) to collect data from sensor nodes where the MDC reaches a set of data collection points (DCPs) to collect data from nearby nodes. This strategy has resolved the underlying cause

Machine Learning (ML) techniques have changed the analysis of massive data in the Internet of Things (IoT) environment very effectively. In the IoT theme of applications, reducing latency and energy consumption are the two crucial network Quality of Service (QoS) parameters and the most significant challenges because they directly impact the users’ experience. Enabling intelligence at the IoT fog computing

The single recent focus on deep learning accuracy ignores economic, and environmental cost. Progress towards Green AI is hindered by lack of universal metrics that equally reward accuracy and cost and can help to improve all deep learning algorithms and platforms. We define recognition and training efficiency as new universal metrics to assess deep learning sustainability and compare them to similar

Forecasting the energy generation from the solar power is considered challenging due to inaccuracies in forecasting, reliability issues and substantial economic losses in power systems. Hence, it is necessary to consider wide features from the solar power generation point of view. In this paper, the study uses large features set to feed the deep learning classifier for optimal prediction of energy

Pipeline leakage incidents have led to serious environmental concerns, prompting the development of various methods to detect leakage in pipelines. Hence, there is a justified need for early leakage detection as well as leakage prediction system. Many of the leak detection techniques are based on computational intelligence techniques such as artificial neural networks, support vector machine, and fuzzy

This paper optimizes the throughput of cooperative cognitive radio networks (CRN). There are multiple branches and multiple hops. Transmission is performed on the branch with the highest signal to interference plus noise ratio (SINR). Secondary source and relays have multiple receiving antennas to harvest energy from radio frequency (RF) signal received from primary transmitter PT. These secondary

Smart phones are widely used but they still suffer from constrained resources in term of their processing capabilities, memory capacity and battery capacity. Mobile Cloud Computing (MCC) has recently emerged to overcome the shortcomings of the standalone smartphones, where Cloud Computing (CC) is leveraged for processing capabilities and memory capacity, while the smartphone would use minimal battery

Smartphones and portable devices have been widely used in our daily life. However, these portable devices cannot be used in a lot of environments due to limitations in battery capacity and computing speed. Therefore, how to save energy consumption and improve processing ability has become a hot issue. The previous works were mainly to transfer some local tasks to remote compute nodes by intelligently

The energy consumption of network devices is a significant part of the network's energy costs. Recently, Software-Defined Networking (SDN) has been suggested as a suitable and stable solution to decrease energy consumption. The main concern is how to manage resources for optimum energy consumption in SDN. Hence, this paper proposes a binary linear programming model. This model manages (on or off devices)

The application of remaining useful life (RUL) prediction is very important in terms of energy optimization, cost-effectiveness, and risk mitigation. The existing RUL prediction algorithms mostly constitute deep learning frameworks. In this paper, we implement LSTM and GRU models and compare the obtained results with a proposed genetically trained neural network. The current models solely depend on

The technological advancements have led to a revolutionized change in the field of the health care industry. One of these promising solutions is the Wireless Body Area Networks (WBAN) which has been providing smart healthcare solutions to the consumers. WBAN deals with the sensor nodes that are placed on or embedded into the human body. It is a very challenging task for the sensor nodes to transmit

Fog computing has the capability to provide computing resources to end-to-end devices like Internet-of-Things (IoT), thereby reducing the burden on the cloud. However, due to the growth of IoT devices and an increase in resource consumption, load balancing in fog computing has turned into a challenging task, since improper load allocation may result in underutilization and overutilization while transferring

Clustering is an unsupervised classification technique used to form groups of unlabeled data sets called clusters. K-means algorithm is a popular clustering algorithm in which random cluster centers are initially taken. The cluster centers are randomly picked in most of the clustering techniques for which the results obtained by these techniques might be compromised. In clustering techniques, the cluster

This paper models the task assignment based on guessing size (TAGS) job allocation algorithm using Markovian processing algebra; PEPA. It aims to analyse performance and energy consumption. The working environment is assumed to be heterogeneous, and the job size distribution is assumed to be a two phase hyper-exponential. Furthermore, the queues are bounded. A two nodes system is implemented with exponentially

Bio-impedance is a method to assess the body composition safely, non-invasively and inexpensively. This method finds application for assessing body fluid and body composition for multiple disease scenarios in clinical environments and for at-home monitoring of chronic ailments. Bio-impedance sensors require higher power than most other bio-signal acquisition systems due to need of high frequency current

Renewable and sustainable energy with advancement in information and communication technologies bear huge expectations in power sector. Whereas, switching from traditional to networked power grid requires a long process. Currently, renewable energy (RE) injection into existing power systems is in transition state, which is a sophisticated and multidisciplinary task. In this article, RE integration

Software is a fundamental part of today's society. However, both users and software professionals need to be aware that its use impacts on the environment, due to the high energy consumption it entails. One of the main gaps to be faced is the difficulty of analyzing software energy consumption in the endeavor to know whether a particular software product is as much energetically efficient as possible

Extreme precipitation is a major challenge affecting the normal functions of urban transportation, particularly in the context of climate change. National and municipal administrations have responded to the increased probability of extreme precipitation events by expanding drainage facilities, or by warning the public in time. In this study, we applied a dynamic system framework to examine how the

At present, rural areas in China have problems such as poor living environment, shortage of facilities, and industrial disappointment. They still use the concept and strategy of urban planning and design to manage the rural areas, which leads to the rural planning results become empty shells, which is time-consuming and laborious, but does not bring practical use to the improvement of rural life. The

In this paper, a hybrid technique is proposed for the system modeling and energy management of Microgrid (MG) connected sources. The proposed hybrid technique is the hybridization of Artificial Bees Colony (ABC) with Bat Search Algorithm (BAT) and Artificial Neural Network (ANN). Here, the novelty of the proposed method is that the search space of the scout bees is gained with the utilization of the

Nowadays, waste to energy (WTE) transformation solutions play a vital role in waste disposal. Accurate WTE resource planning can be made using high-performance waste amount prediction models. Thus, a significant gain can be obtained both in economic and environmental terms. In this paper, we proposed different machine learning models to predict the amount of municipal solid waste (MSW) to be used for

Reducing computational energy consumption in cyber-physical systems (CPSs) has attracted considerable attention in recent years. Associated with energy consumption is a heating of the devices. Device failure rate increases exponentially with increase temperature, so that high energy consumption leads to a significant shortening of processor lifetime. Reducing thermal stress without harming application

The pandemic of coronavirus has dramatically disrupted the retail industry, as many stores are forced to close and people across the world are shelter-in-place with online shopping as the inevitable choice. To meet the rapidly increasing demand for e-commerce, more data centers are expected to provide new or significantly improve existing cloud services that can better support hybrid workloads (e.g

Source code improvements can be suggested or automatically applied from within an IDE augmenting the skills of a developer. In addition, compiler optimizations are readily available for a variety of languages and programming environments that continue to enhance a developer's code on the back end. Common optimizations include transformations that automatically improve the speed or lower the memory

In the past years, the supply of Chinese herbal medicine has become more and more significant. In order to promote the standardized production of Chinese herbal medicine, we should take effective quality control on its production, processing and purchase. It is difficult to control the production quality and production standards of various Chinese herbal medicines planted separately. It is imperative

In this article, a low power, area-efficient full adder cell designed with approximate outputs is presented. The static Complementary Metal Oxide Semiconductor (CMOS) structure is applied to design this approximate full adder energy efficient (up to 72% improvement). The proposed cell simulated in HSPICE with 32nm CMOS technology in four different scenarios. First, the proposed cell was assessed as

With the proliferation of data produced by IoT devices, a new paradigm called fog computing has developed that allows processing and analysis of data at the edge. Together with fog, cloud computing co-exists for purposes such as enormous storage, processing resources, etc. However, storage and computation of data at various levels increase the risk of data privacy. Therefore, an access control mechanism

The food for healthy living, but even with this awareness we a lagging in controlling the food getting wasted every day. It was reported that about 1/3rd of the total food produced in a year is wasted globally, which is an alarming figure and proper measures have to be taken to reduce the waste. In this work we propose a sustainable food waste management system in a college hostel environment, for

Rapid and accurate identification of wheat leaf diseases and their severity is benefit for the precise prevention and control of wheat leaf diseases. Taking powdery mildew and stripe rust as research objects, this study proposes an algorithm for identification of wheat leaf diseases and their severity based on Elliptical-Maximum Margin Criterion (E-MMC) metric learning. Compared with other metrics

Electricity supply must be matched with demand at all times. This helps reduce the chances of issues such as load frequency control and the chances of electricity blackouts. To gain a better understanding of the load that is likely to be required over the next 24h, estimations under uncertainty are needed. This is especially difficult in a decentralized electricity market with many micro-producers

Cloud systems play a vital and significant role in our daily lives due to various internet services. For instance, email services, social networks, and others. Consequently, their energy consumption has also become an increasingly essential concern in Cloud Computing Systems (CCSs). Virtualization technologies are widely used to facilitate the management of CCSs and reduce their energy consumption

Railway is currently envisioned as the most promising transportation system for both people and freight to reduce atmospheric emission and combat climate change. In this context, ensuring the energy efficiency of the railway systems is paramount in order to sustain their future expandability with minimum carbon footprint. Recent advancements in computing and communication technologies are expected

Wireless body area network (WBAN) is growing enormously with the technical development of the internet of things (IOT). On body WBAN is one of the types in which sensors are located on the body of patient. Cooperative techniques are useful in mitigating the fading effect and improving the quality of the transmitted signal. In the current work, a mathematical model considering cooperative CM3A operating

Accurate and efficient Machine Learning algorithms are of vital importance to many problems, especially on classification or clustering tasks but need a universal AI model standard. Unifying machine learning models into a common ecosystem can lead to less development time and better framework interoperability. ONNX (Open Neural Network Exchange Format) is a popular open format to represent deep learning

The development of in chip manufacturing processes has enhanced energy-efficient nano-electronic and high-performance devices in daily activities. In recent times, CMOS technology scaling has recognized several transistors in large-scale VLSI chips to support performance. However, these innovations have also frequently increased the impact of Soft-Error (SE) reliability concerns in computing architectures

With the rapid increase of the number of people on the earth, the environment is deteriorating gradually, and there is a shortage of resources. Therefore, it is urgent to actively participate in the creation of efficient energy-saving technology. The purpose of this article is to study the role of high-efficiency and energy-saving architecture in corporate brand building, explore the relationship between

In virtualized cloud computing systems, energy reduction is a serious concern since it can offer many major advantages, such as reducing running costs, increasing system efficiency, and protecting the environment. At the same time, an energy-efficient task scheduling strategy is a viable way to meet these goals. Unfortunately, mapping cloud resources to user requests to achieve good performance by

Nowadays, China's economic development is in a rapid and stable state, in which scientific and technological innovation has played a great role in promoting the development of economic society. Scientific and technological innovation is an important indicator to measure the competitiveness of modern economic society, and is also the pillar and driving force for the survival of regional economic development

In this work, we propose a two-step methodology for designing and sizing a data center solely powered by local renewable energy. The first step consists in determining the necessary IT equipment for processing a given IT workload composed of batch and service tasks. We propose an adapted binary search algorithm and prove its optimality to find the minimum number of servers to handle the IT workload

Evaporation from sub-surface reservoirs is a phenomenon that has drawn a considerable amount of attention, over recent years. An accurate prediction of the sub-surface evaporation rate is a vital step towards drawing better managing of the reservoir’ water system. In fact, the evaporation rate and more specifically from sub-surface is considered as highly stochastic and non-linear process that affected

Wearable wireless sensors, or Wireless Body Sensor Network (WBSN), is one of the most recent fields of research in healthcare applications. The sensors are placed on the human body to detect the critical medical parameters and transmit the collected data to a centralized node. Though the devices work at low energy and power constraints, maintenance of such devices is a crucial aspect. In light of this

In recent years, China's economy continues to develop at a high speed, but also faces the enormous pressure of energy shortage and environmental deterioration. As an energy-saving discipline, we should actively adopt advanced energy-saving management methods and technologies for energy utilization management. The purpose of this paper is to study an integrated energy pipeline system based on Internet

Security vulnerability prediction models allow estimation of the number of potential vulnerabilities and evaluation of the risks caused by these vulnerabilities. In particular, for modeling the vulnerabilities that may occur in software versions over time, it is appropriate to take the necessary countermeasures. These models are crucial in areas such as determining the number of resources required

In this work, we present a real-time embedded implementation of an algorithm dedicated to monitoring agricultural fields. This algorithm is based on normalized indices, such as the Normalized Difference Vegetation Index (NDVI) and the Normalized Difference Water Index (NDWI). The problem of most algorithms in this context is real-time processing, especially when we talk about applications that require

Cloudlet is an important part of providing cloud services in Mobile Edge Computing (MEC) with sustainability. As the number of mobile users grows rapidly in the current era, the load in the cloudlet becomes very high. The cloudlet is considered in the middle layer for providing cloud services with low latency and energy efficiency. Hence the task allocation and scheduling inside of the cloudlet is

In this paper, we have proposed a DRL based method to obtain the route based on an optimized load of SDN which is based on self-learning of human intelligence. In this proposal, the Bio-Inspired RBM is used for Bio-Inspired Deep Belief Architecture (BDBA) for implementing deep learning to obtain the optimized route. This Bio-Inspired RBM has two parts one is simple RBM and another part is inspired

Opportunism in the Internet of Things is the latest necessity arising in the IoT network communication development when we encompass a sustainable approach to routing. Such a requirement arises from the need for device-hop based networking to eliminate a dedicated end-to-end physical network for pervasive communication and promotes local data and computation sharing mechanisms as well as sustainably

In order to provide a basis for the development of mineral resources and the implementation of spatial zoning management, the application of fuzzy recognition method in mineral resources allocation is studied and analyzed in this study to promote the optimal allocation of mineral resources and establish a reasonable regional division of labor and cooperation relationship. The results show that, taking