Worldwide, energy consumption and saving represent the main challenges for all sectors, most importantly in industrial domestic sectors. The internet of things (IoT) is a new technology that establishes core Industry 4.0. IoT enables sharing signals between devices machines via internet. Besides, system utilization artificial intelligence (AI) techniques to manage control different based on decisions. paper’s innovation introduce deep learning approach operation air conditioners order reduce...

The modern control infrastructure that manages and monitors the communication between smart machines represents most effective way to increase efficiency of industrial environment, such as grids. cyber-physical systems utilize embedded software internet connect are addressed by things (IoT). These basis fourth revolution which is indexed industry 4.0. In particular, 4.0 relies heavily on IoT sensors energy meters. reliability security represent main challenges face implementation. This paper...

In recent years, the internet of things (IoT) represents main core Industry 4.0 for cyber-physic systems (CPS) in order to improve industrial environment. Accordingly, application IoT and CPS has been expanded applied electrical machines. However, cybersecurity challenge implementation against cyber-attacks. this regard, paper proposes a new architecture based on utilizing machine learning techniques suppress cyber-attacks providing reliable secure online monitoring induction motor status....

This paper introduces a new intelligent integration between an IoT platform and deep learning neural network (DNN) algorithm for the online monitoring of computer numerical control (CNC) machines. The proposed infrastructure is utilized cutting process while maintaining stability CNC machines in order to ensure effective processes that can help increase quality products. For this purpose, force sensor installed milling machine center measure vibration conditions. Accordingly, architecture...

Deep learning is a cutting-edge image processing method that still relatively new but produces reliable results. Leaf disease detection and categorization employ variety of deep approaches. Tomatoes are one the most popular vegetables can be found in every kitchen various forms, no matter cuisine. After potato sweet potato, it third widely produced crop. The second-largest tomato grower world India. However, many diseases affect quality quantity crops. This article discusses...

Power transformer represents an important equipment in electric power systems. Transformers are not only a source of outages for utilities, but they also affect customers because interrupt supplies. require frequent maintenance and service, which can be time-consuming expensive. systems their servicing planned advance when faults detected early with high accuracy rates. In order to avoid unplanned shutdowns, it is crucial monitor diagnose transformers. Based on how electrical thermal...

Automated guided vehicles (AGVs) have become a key part of many industries, where they handle the task managing material flows. As result, are very important targets for cyberattacks to cripple organizations by using methods, such as false data injection (FDI) and denial service (DoS) on sensors measurement data. This article introduces new robust Kalman filter (KF) AGV state estimation Huber loss function. A statistical method known M-estimation is used solve regression issue robustly...

Wind speed fluctuations and load demand variations represent the big challenges against wind energy conversion systems (WECS). Besides, inefficient measuring devices environmental impacts (e.g. temperature, humidity, noise signals) affect system equipment, leading to increased uncertainty issues. In addition, time delay due communication channels can make a gap between transmitted control signal WECS that causes instability for operation. To tackle these issues, this paper proposes an...

The tuning of the robot actuator represents many challenges to follow a predefined trajectory on account uncertainties parameters and model nonlinearity. Furthermore, controller gains require proper optimization achieve good performance. In this paper, use modified neural network algorithm (MNNA) is proposed as novel adaptive optimize gains. new mathematical modulation introduced promote exploration manner NNA without initial parameters. Specifically, formed by using polynomial mutation....

Recently, the Internet of Things (IoT) has an important role in growth and development digitalized electric power stations while offering ambitious opportunities, specifically real-time monitoring cybersecurity. In this regard, paper introduces a novel IoT architecture for online gas-insulated switchgear (GIS) status instead traditional observation methods. The proposed is derived from concept cyber-physic system (CPS) Industry 4.0. However, cyber-attacks classification GIS insulation...

This paper introduces a robust model predictive controller (MPC) to operate an automatic voltage regulator (AVR). The design strategy tends handle the uncertainty issue of AVR parameters. Frequency domain conditions are derived from Hermite–Biehler theorem maintain stability perturbed system. tuning MPC parameters is performed based on new evolutionary algorithm named arithmetic optimization (AOA), while expert designers use trial and error methods achieve this target. constraints handled...

This paper introduces an integrated IoT architecture to handle the problem of cyber attacks based on a developed deep neural network (DNN) with rectified linear unit in order provide reliable and secure online monitoring for automated guided vehicles (AGVs). The DNN new approach AGVs against cheap easy implementation instead traditional attack detection schemes literature. proposed is trained experimental AGV data that represent real state different types including random attack, ramp pulse...

Two modern methods of the energy management system (EMS) based on a modified cost function are addressed in this paper. Fuzzy logic (FL) and Harris Hawks Optimization (HHO) is implemented to achieve optimal performance seawater desalination plants (SWDP) within minimum feed-in tariff (FiT). The technical difficulties involved variation price from one time another parameters uncertainties. For example, higher at peak lower normal times. Also, can change day day. proposed deal with these...

Demand side management (DSM) has become one of the major concerns smart grids to cope with penetration renewable energy. The availability new communication technologies can enhance resilient operation for DSM. However, false injection data and adversarial attacks that are against signal analysis models represent biggest challenge resiliency energy operations by deploying these in grids. In this regard, article proposes a reliable industrial Internet Things (IoT) architecture deep convolution...

Nowadays, the operation and control of power systems are a big challenge. An essential part system (PS) is load frequency (LFC). Different secondary controllers implemented for problem. Hence, cascaded two-degree freedom tilt-integral-derivative controller having filter (2DOFTIDF) intended in this paper control. In order to determine efficiency 2DOFTIDF controller, well-known non-reheat thermal with/without governor dead band considered. A new whale optimization algorithm (WOA) used enhance...

The effectiveness of positioning techniques that utilize the receiver signal strength (RSS) is highly dependent on instability received indicator (RSSI). Up to now, there no strategy effectively lowers influence such accuracy positioning. Moreover, recent studies showed indoor are vulnerable noise in RSSI data and cyber-attacks, which make them more expensive. In this study, a new internet things (IoT) paradigm proposed for automated guided vehicles (AGVs) using deep convolution neural...