Technology has played a vital part in improving quality of life, especially healthcare. Artificial intelligence (AI) and the Internet Things (IoT) are extensively employed to link accessible medical resources deliver dependable effective intelligent Body wearable devices have garnered attention as powerful for healthcare applications, leading various commercially available multiple purposes, including individual healthcare, activity alerts, fitness. The paper aims cover all advancements made...

Wireless based sensor networks contain sensors for environment monitoring but have restricted resources. Many clustering protocols are designed to prolong network lifetime problems of inadequate cluster head selection criteria, fixed clustering, and static rounds which consume more energy. It is needed develop an adaptive strategy better CH load balancing. In this article, we introduced energy-efficient mobility mechanism overcome these limitations. on dedicated parameters that a huge impact...

Abstract In the human immune system, white blood cells (WBC) creates bone and lymphoid masses. These defend body toward several infections, such as fungi bacteria. The popular WBC types are Eosinophils, Lymphocytes, Neutrophils, Monocytes, which manually diagnosis by experts. manual process is complicated time‐consuming; therefore, an automated system required to classify these WBC. this article, a new method presented for classification using feature selection extreme learning machine...

Most of the IoT‐based smart systems require low latency and crisp response time for their applications. Achieving demand this high Quality Service (QoS) becomes quite challenging when computationally intensive tasks are offloaded to cloud execution. Edge computing therein plays an important role by introducing network latency, quick response, bandwidth. However, offloading computations at a large scale overwhelms edge server with many requests scalability issue originates. To address above...

Industrial Internet of Things (IIoT) applications consist resource constrained interconnected devices that make them vulnerable to data leak and integrity violation challenges. The mobility, dynamism, complex structure the network further this issue more challenging. To control information flow in such environments, access is critical collaboration communication safe. deal with these challenges, recent studies employ attribute-based on top blockchain technology. However, frameworks suffer...

The recent advancements in the Internet of Things have made it converge towards critical infrastructure automation, opening a new paradigm referred to as Industrial (IIoT). In IIoT, different connected devices can send huge amounts data other back and forth for better decision-making process. such use cases, role supervisory control acquisition (SCADA) has been studied by many researchers years robust management. Nevertheless, sustainability these applications, reliable exchange is crucial...

In today’s world, security is the most prominent aspect which has been given higher priority. Despite rapid growth and usage of digital devices, lucrative measurement crimes in under-developing countries still challenging. this work, unstructural crime data (900 records) from news archives previous eight years were extracted to predict behavior criminals’ networks transform it into useful information using natural language processing (NLP). To estimate next move criminals Pakistan, we...

Sarcasm has a significant role in human communication especially on social media platforms where users express their sentiments through humor, satire, and criticism. The identification of sarcasm is crucial comprehending the sentiment context like Twitter. This ambiguous nature expression content presents detection as considerable challenge natural language processing (NLP). importance challenges increase further, languages Urdu resources for NLP are limited. traditional rule-based...

Energy efficiency in buildings depends on the way building is operated. Therefore energy management key component for efficient operation. Data analysis of operation data helps to better understand systems and detect faults inefficiencies. The facility manager benefits from smart that makes use machine learning algorithms innovative visualizations. This part a bigger review current structure automation as it used today's buildings. targets are complex, ambiguous contradictory: indoor...

To achieve energy efficiency in buildings, a lot of raw data is recorded, during the operation buildings. This recorded further used for analysis performance buildings and its different components e.g. Heating, Ventilation Air-Conditioning (HVAC). save time it required to ensure resilience by detecting replacing outliers (i.e. samples that are not plausible) before detailed analysis. paper discusses steps involved obtained from absorption chiller using their On/Off state information. It also...

Building automation systems record operation data including physical values, system states and conditions. This is stored, but commonly not automatically evaluated. historic the key to efficient quick recognition of errors inefficiencies, a potential that exploited today. Instead, today evaluation during delivers only alarming in case failures. Analysis done by facility manager, who uses his experience interpret data. Methods from mining analysis can contribute better understanding building...

Abstract Purpose Due to the large quantity of data that are recorded in energy efficient buildings, understanding behavior various underlying operations has become a complex and challenging task. This paper proposes method support analysis systems validates it using operational from cold water chiller. The automatically detects operation patterns system. Methods use k-means clustering is being proposed identify On (operational) cycles system operating with duty cycle. latter’s subsequently...

The secure communication of information is a major concern over the internet.The must be protected before transmitting channel to avoid security violations.In this paper, new hybrid method called compressed encrypted data embedding (CEDE) proposed.In CEDE, secret first with Lempel Ziv Welch (LZW) compression algorithm.Then, using Advanced Encryption Standard (AES) symmetric block cipher.In last step, embedded into an image size 512 × pixels by steganography.In steganographic technique, and...

Machine Learning (ML)-based prediction and classification systems employ data learning algorithms to forecast target values. However, improving predictive accuracy is a crucial step for informed decision-making. In the healthcare domain, are available in form of genetic profiles clinical characteristics build models complex tasks like cancer detection or diagnosis. Among ML algorithms, Artificial Neural Networks (ANNs) considered most suitable framework many tasks. The network weights...

Recent advances in Generative Adversarial Networks (GANs) have produced synthetic images with high visual fidelity, making them nearly indistinguishable from human-created images. These referred to as deepfakes, become a major source of misinformation due social media. Technology is advancing rapidly, so reliable methods for distinguishing real fake are needed. The current detection mechanisms require image forensics tools such error level analysis (ELA), and clone detect manipulated...

The potential of demand side as a frequency reserve proposes interesting opportunity in handling imbalances due to intermittent renewable energy sources. This paper novel approach for computing the parameters stochastic battery model representing aggregation Thermostatically Controlled Loads (TCLs). A hysteresis based non-disruptive control is used using priority stack algorithm track reference regulation signal. admissible ramp-rate and charge limits are dynamically calculated information...