The recent advances in embedded processing have enabled the vision based systems to detect fire during surveillance using convolutional neural networks (CNNs). However, such methods generally need more computational time and memory, restricting its implementation networks. In this research paper, we propose a cost-effective detection CNN architecture for videos. model is inspired from GoogleNet architecture, considering reasonable complexity suitability intended problem compared other...

The electric energy consumption prediction (EECP) is an essential and complex task in intelligent power management system. EECP plays a significant role drawing up national development policy. Therefore, this study proposes Electric Energy Consumption Prediction model utilizing the combination of Convolutional Neural Network (CNN) Bi-directional Long Short-Term Memory (Bi-LSTM) that named EECP-CBL to predict consumption. In framework, two CNNs first module extract important information from...

Deep learning methods, e.g., convolutional neural networks (CNNs) and Recurrent Neural Networks (RNNs), have achieved great success in image processing natural language especially high level vision applications such as recognition understanding. However, it is rarely used to solve information security problems attack detection studied this paper. Here, we move forward a step propose novel multi-channel intelligent method based on long short term memory recurrent (LSTM-RNNs). To achieve rate,...

As the next generation network architecture, software-defined networking (SDN) has exciting application prospects. Its core idea is to separate forwarding layer and control of system, where operators can program packet behavior significantly improve innovation capability applications. Traffic engineering (TE) an important application, which studies measurement management traffic, designs reasonable routing mechanisms guide traffic utilization resources, better meet requirements quality...

Due to industrialization and the rising demand for energy, global energy consumption has been rapidly increasing. Recent studies show that biggest portion of is consumed in residential buildings, i.e., European Union countries up 40% total by households. Most buildings industrial zones are equipped with smart sensors such as metering electric sensors, inadequately utilized better management. In this paper, we develop a hybrid convolutional neural network (CNN) an long short-term memory...

Excessive Power Consumption (PC) and demand for power is increasing on a daily basis, due to advancements in technology, the rise electricity-dependent machinery, growth of human population. It has become necessary predict PC order improve management co-operation between energy used building grid. State-of-the-art Energy Prediction (ECP) methods are limited terms predicting effectively, various challenges such as weather conditions dynamic behaviour occupants. Thus, overcome drawbacks these...

To resolve the contradictions between increasing demand of vehicular wireless applications and shortage spectrum resources, high mobility, short link lifetime, efficiency, a novel cognitive radio (CR) efficient management in communication is required. Therefore, to exhibit importance spectral system model proposed for cooperative centralized distributed sensing networks. The architecture used minimize both scarcity mobility issues. Furthermore, we analyze decision fusion techniques In...

Flying ad-hoc networks (FANETs) are a very vibrant research area nowadays. They have many military and civil applications. Limited battery energy the high mobility of micro unmanned aerial vehicles (UAVs) represent their two main problems, i.e., short flight time inefficient routing. In this paper, we try to address both these problems by means efficient clustering. First, adjust transmission power UAVs anticipating operational requirements. Optimal range will minimum packet loss ratio (PLR)...

Wireless sensor networks (WSNs) are widely used in the area of health informatics. and wearable sensors have become prevalent devices to monitor patients at risk for chronic diseases. This helps ascertain that comply by treatment plans also safeguard them during sudden attacks. The amount data gathered from various is numerous. In this paper, we propose use fog computing help suffering diseases such collected processed an efficient manner. main challenge would be only sort out...

Cloud-based healthcare service with the Internet of Healthcare Things (IoHT) is a model for delivery urban areas and vulnerable population that utilizes digital communications IoHT to provide flexible opportunities transform all health data into workable, personalized insights, help attain wellness outside traditional hospital setting. This Web services acts like living organism, taking advantage afforded by running in cloud infrastructure connect patients providers anywhere anytime improve...

Smart cities are a future reality for municipalities around the world. Healthcare services play vital role in transformation of traditional into smart cities. In this paper, we present ubiquitous and quality computer-aided blood analysis service detection counting white cells (WBCs) samples. WBCs also called leukocytes or leucocytes immune system that involved protecting body against both infectious disease foreign invaders. Analysis provides valuable information to medical specialists,...

The intermittent and uncertain nature of wind places a premium on accurate power forecasting for the reliable efficient operation grids with large-scale penetration. Herein, six-month-ahead models were developed using tree-based learning algorithms. Three to investigate impact input data accuracy. first model was trained average standard deviation speed values measured at height 40 m 10-min sampling time. To evaluate time performance, second 1-h, 12-h, 24-h times. assess effect measuring...

Movies have become one of the major sources entertainment in current era, which are based on diverse ideas. Action movies received most attention last few years, contain violent scenes, because it is undesirable features for some individuals that used to create charm and fantasy. However, these scenes had a negative impact kids, they not comfortable even mature age people. The best way stop under aged people from watching eliminate scenes. In this paper, we proposed violence detection scheme...

Blockchain and the Internet of Things (IoT) are separately regarded as highly capable popular technologies. is a database used for decentralized transaction purposes. It provides novel directions to store manage data, whereas IoT relates propagation linked machines by providing information through Internet. A mixture appears hopeful, even though blockchain requires real-time data application, describes processes overloads safely proficiently. The technology significant manufacturing...

Smart grids have recently attracted increasing attention because of their reliability, flexibility, sustainability, and efficiency. A typical smart grid consists diverse components such as meters, energy management systems, storage renewable resources. In particular, to make an effective strategy for the system, accurate load forecasting is necessary. Recently, artificial neural network–based models with good performance been proposed. For forecasting, it critical determine hyperparameters...

Smart grid technology based on renewable energy and storage systems are attracting considerable attention towards crises. Accurate reliable model for electricity prediction is considered a key factor suitable management policy. Currently, consumption rapidly increasing due to the rise in human population development. Therefore, this study, we established two-step methodology residential building load prediction, which comprises two stages: first stage, raw data of refined effective training;...