Responsible, efficient and environmentally aware energy consumption behavior is becoming a necessity for the reliable modern electricity grid. In this paper, we present an intelligent data mining model to analyze, forecast visualize time series uncover various temporal patterns. These patterns define appliance usage in terms of association with such as hour day, period weekday, week, month season year well appliance-appliance associations household, which are key factors infer analyze impact...

Nowadays, there is an ever-increasing migration of people to urban areas. Health care service one the most challenging aspects that greatly affected by vast influx city centers. Consequently, cities around world are investing heavily in digital transformation effort provide healthier ecosystems for people. In such a transformation, millions homes being equipped with smart devices (e.g., meters, sensors, and so on), which generate massive volumes fine-grained indexical data can be analyzed...

Accurate methods to measure food and energy intake are crucial for the battle against obesity. Providing users/patients with convenient intelligent solutions that help them their collect dietary information most valuable insights toward long-term prevention successful treatment programs. In this paper, we propose an assistive calorie measurement system patients doctors succeed in fight diet-related health conditions. Our proposed runs on smartphones, which allow user take a picture of amount...

Ambient intelligence (AmI) considers responsive environments in which applications and services adapt their behavior according to the user's needs changing context. One of most challenging aspects for many AmI is location orientation surrounding objects. This especially important effective cooperation among mobile physical objects such smart environments. In this paper, we propose a robust indoor positioning system that provides 2-D information The utilizes low-range passive radio frequency...

Network and cloud service providers are facing an unprecedented challenge to meet the demand of end-users during COVID-19 pandemic. Currently, billions people around world ordered stay at home use remote connection technologies prevent spread disease. The crisis brought a new reality network that will eventually accelerate deployment edge computing resources attract massive influx users' traffic. user can elect procure its resource needs from any provider based on variety attributes such as...

Fruit that has reached maturity is ready to be harvested. The prediction of fruit and quality important not only for farmers or the food industry but also small retail stores supermarkets where fruits are sold purchased. classification process by which classified according their in life cycle. Nowadays, deep learning (DL) been applied many applications smart agriculture such as water soil management, crop planting, disease detection, weed removal, distribution, strong counting, harvesting,...

The fast-growing electric vehicles (EVs) industry requires a well-designed recommendation system to locate charging stations while ensuring private data protection. This article proposes secure cloudlet-based for EVs. Unlike conventional methods where training recommender model involves direct sharing between holders, our utilizes vertical federated learning technique, in which EVs do not leave the platforms. To improve efficiency of and alleviate communication-related concerns model,...

The Internet of Things (IoT) uses wireless networks without infrastructure to install a huge number sensors that track system, physical, and environmental factors. There are variety WSN uses, some well-known application factors include energy consumption lifespan duration for routing purposes. have detecting, processing, communication capabilities. In this paper, an intelligent healthcare system is proposed which consists nano collect real-time health status transfer it the doctor's server....

Electric vehicles (EVs) are the backbone of future intelligent transportation system (ITS). They environmentally friendly and can also be integrated as distributed energy resources (DERs) into smart grid using vehicle-to-grid (V2G) scheme. Specifically, utility companies push back EV batteries electric to reduce peak load. However, integrating EVs power efficiently requires accurate artificial intelligence (AI) mechanisms forecast, coordinate, dispatch grid. This paper proposes a Multi-agent...

Throughout various complex processes within hospitals, context-aware services and applications can help to improve the quality of care reduce costs. For example, sensors radio frequency identification (RFID) technologies for e-health have been deployed flow material, equipment, personal, patient. Bed tracking, patient monitoring, real-time logistic analysis, critical equipment tracking are famous location systems (RTLS) in hospitals. In fact, existing case studies show that RTLS service...

Next generation networks such as Software Defined Networks (SDN) must support the integration of new paradigms service offerings virtual cloud computing, big data applications, centers services, and rich multimedia content. Operators next SDNs are responsible for configuring policies that employ traffic monitoring tools measurement mechanisms to detect react a wide range network events applications. In this article, we take look at methods in SDNs, cover their strengths weaknesses, point...

Inarguably, buying-in consumer confidence through respecting their energy consumption behavior and preferences in various programs is imperative but also demanding. Household patterns, which provide great insight into consumers behavioral traits, can be learned by understanding user activities along with appliances used time of use. Such information retrieved from the context-rich smart meters big data. However, main challenge how to extract complex interdependencies among multiple operating...

Automated food and drink recognition methods connect to cloud-based lookup databases (e.g., item barcodes, previously identified images, or classified NIR (Near Infrared) spectra of items databases) match identify a scanned item, report the results back user. However, these remain limited value if we cannot further reason with items, ingredients quantities/portion sizes in proposed meal various contexts; i.e., understand from semantic perspective their types, properties, interrelationships...

Aggregating fine-granular data measurements from smart meters presents an opportunity for utility companies to learn about consumers' power consumption patterns. Several research studies have shown that patterns can reveal a range of information consumers, such as how many people are in the home, types appliances they use, their eating and sleeping routines, even TV programs watch. As we move toward liberalized energy markets, different parties interested gaining access data, which has...

In the Internet of Things (IoT), de facto Routing Protocol for Low Power and Lossy Networks (RPL) is susceptible to several disruptive attacks based on its functionalities features. Among various RPL security solutions, a trust-based easy adapt resource-constrained IoT environments. existing routing attacks, nodes' mobility not considered or limited only sender nodes. Similarly, these protocols are evaluated mobile environments, particularly regarding attacks. Hence, trust mobility-based...

The proliferation of electric vehicles (EVs) and the advancement Vehicle-to-Everything (V2X) energy trading systems are expected to play a crucial role in alleviating stress on grid during peak hours. However, wide adoption these paradigms requires intelligent mechanisms that protect security privacy EV users. This paper proposes novel Federated Reinforcement Learning (FRL) system combined with blockchain technology maximize users' utility while preserving transactions. Furthermore, we...

The Internet of Things (IoT) and the Electric Vehicle (EV) industry are critical to rapid growth consumer-centric Vehicles (IoV) services facilitate 6G-enabled vehicle communication, which offers numerous advantages. Among applications (IoV), a recommendation system is introduced identify nearby charging sources while preserving user privacy, crucial aspect IoV framework security. Determining suggest an EV (as consumer electronics) challenging issue, given potential recommendations...