The Internet of Things (IoT) ecosystem has experienced significant growth in data traffic and consequently high dimensionality. Intrusion Detection Systems (IDSs) are essential self-protective tools against various cyber-attacks. However, IoT IDS systems face challenges due to functional physical diversity. These characteristics make exploiting all features attributes for self-protection difficult unrealistic. This paper proposes implements a novel feature selection extraction approach...

Skin cancer is among the most prevalent and life-threatening forms of that occur worldwide. Traditional methods skin detection need an in-depth physical examination by a medical professional, which time-consuming in some cases. Recently, computer-aided diagnostic systems have gained popularity due to their effectiveness efficiency. These can assist dermatologists early cancer, be lifesaving. In this paper, pre-trained MobileNetV2 DenseNet201 deep learning models are modified adding...

Today, disease detection automation is widespread in healthcare systems. The diabetic a significant problem that has spread widely all over the world. It genetic causes trouble for human life throughout lifespan. Every year number of people with diabetes rises by millions, and this affects children too. identification involves manual checking so far, current trend medical field. Existing methods use single algorithm prediction diabetes. For complex problems, model not enough because it may...

Recently, Internet of Things (IoT) and cloud computing environments become commonly employed in several healthcare applications by the integration monitoring things such as sensors medical gadgets for observing remote patients. For availing improved services, huge count data generated IoT from medicinal field can be investigated CC environment rather than relying on limited processing storage resources. At same time, earlier identification chronic kidney disease (CKD) becomes essential to...

Applied sensing technology has made it possible for human beings to experience a revolutionary aspect of the science and world. Along with many other fields in which this is working wonders, locomotion activity recognition, finds applications healthcare, smart homes, life-logging, fields, also proving be landmark. The purpose study develop novel model that can robustly handle divergent data are acquired remotely from various sensors make an accurate classification activities. biggest support...

More adaptable and user-independent techniques are required for multi-sensors based daily locomotion detection (MS-DLD). This research study proposes a couple of methods using body-worn to successfully categorize several transitions. presents both standard state-of-the-art MS-DLD. Conventionally, improve MS-DLD process, the proposed methodology consists wavelet transformed Quaternion-based filter inertial signals, patterns recognition in form kinematic-static energies, multi-features...

Event detection systems are mainly used to observe and monitor human behavior via red green blue (RGB) images videos. using RGB is one of the challenging tasks current era. Human detection, position orientation body parts in a critical phase for numerous models. In this research article, by extracting context-aware energy features event recognition described. For this, silhouette extraction, estimation parts, extracted. To optimize context-intelligence vector, we applied an artificial...

The latest visionary technologies have made an evident impact on remote sensing scene classification. Scene classification is one of the most challenging yet important tasks in understanding high-resolution aerial and scenes. In this discipline, deep learning models, particularly convolutional neural networks (CNNs), outstanding accomplishments. Deep feature extraction from a CNN model frequently utilized technique these approaches. Although CNN-based techniques achieved considerable...

In the past two decades, there has been a lot of work on computer vision technology that incorporates many tasks which implement basic filtering to image classification. The major research areas this field include object detection and recognition. Moreover, wireless communication technologies are presently adopted they have impacted way education changed. There different phases changes in traditional system. Perception three-dimensional (3D) from two-dimensional (2D) is one demanding tasks....

With the increasing online activity of Arabic speakers, development effective CAPTCHAs (Completely Automated Public Turing Tests to Tell Computers and Humans Apart) tailored for users has become crucial. Traditional CAPTCHAs, however, are increasingly vulnerable machine learning-based attacks. To address this challenge, we introduce a method generating adversarial handwritten that remain user-friendly yet difficult machines solve. Our approach involves synthesizing words using simulation...

Due to the recently increased requirements of e-learning systems, multiple educational institutes such as kindergarten have transformed their learning towards virtual education. Automated student health exercise is a difficult task but an important one due physical education needs especially in young learners. The proposed system focuses on necessary implementation recognition (SHER) using modified Quaternion-based filter for inertial data refining and fusion pre-processing steps. Further,...

Advanced aerial images have led to the development of improved human–object interaction recognition (HOI) methods for usage in surveillance, security, and public monitoring systems. Despite ever-increasing rate research being conducted field HOI, existing challenges occlusion, scale variation, fast motion, illumination variation continue attract more researchers. In particular, accurate identification human body parts, involved objects, robust features is key effective HOI However,...

The advancements in sensing technologies, information processing, and communication schemes have revolutionized the healthcare sector. Electronic Healthcare Records (EHR) facilitate patients, doctors, hospitals, other stakeholders to maintain valuable data medical records. traditional EHRs are based on cloud-based architectures susceptible multiple cyberattacks. A single attempt of a successful Denial Service (DoS) attack can compromise complete system. This article introduces secure...

With the change of technology and innovation current era, retrieving data processing becomes a more challenging task for researchers. In particular, several types sensors cameras are used to collect multimedia from various resources domains, which have been in different domains platforms analyze things such as educational communicational setups, emergency services, surveillance systems. this paper, we propose robust method predict human behavior indoor outdoor crowd environments. While...

In this research work, an efficient sign language recognition tool for e-learning has been proposed with a new type of feature set based on angle and lines. This the ability to increase overall performance machine learning algorithms in way. The hand gesture these features implemented usage real-time. used landmarks, which were generated using media-pipe (MediaPipe) open computer vision (openCV) each frame incoming video. algorithm tested two well-known ASL-alphabet (American Sign Language)...

<abstract><p>The Internet of Things (IoT) is a paradigm that connects range physical smart devices to provide ubiquitous services individuals and automate their daily tasks. IoT collect data from the surrounding environment communicate with other using different communication protocols such as CoAP, MQTT, DDS, etc. Study shows these are vulnerable attack prove significant threat telemetry data. Within network, interdependent, behaviour one device depends on coming another device....

Robotics is a part of today's communication that makes human life simpler in the day-to-day aspect. Therefore, we are supporting this cause by making smart city project based on Artificial Intelligence, image processing, and some touch hardware such as robotics. In particular, advocate self automation device (i.e., autonomous car) performs actions takes choices its very own intelligence with assist sensors. Sensors key additives for developing upgrading all forms self-sustaining cars...

Wireless communications have lately experienced substantial exploitation because they provide a lot of flexibility for data delivery. It provides connection and mobility by using air as medium. sensor networks (WSN) are now the most popular wireless technologies. They need communication infrastructure that is both energy computationally efficient, which made feasible developing best protocol algorithms. The internet things (IoT) paradigm anticipated to be heavily reliant on networking...

CAPTCHA is a test that can, automatically, tell human and computer programmes apart. It now almost standard security technology, has found widespread application on commercial websites. Robustness usability are two fundamental aspects with CAPTCHA. The robustness of text typically determined by the strength its segmentation-resistance mechanism. mechanism Crowding Character Together (CCT) been shown to be reasonably resistant known attacks. On other hand, such an approach can reduce making...

The critical task of recognizing human–object interactions (HOI) finds its application in the domains surveillance, security, healthcare, assisted living, rehabilitation, sports, and online learning. This has led to development various HOI recognition systems recent past. Thus, purpose this study is develop a novel graph-based solution for purpose. In particular, proposed system takes sequential data as input recognizes interaction being performed it. That is, first all, pre-processes by...

In the past few years, home appliances have been influenced by latest technologies and changes in consumer trends. One of most desired gadgets this time is a universal remote control for gestures. Hand gestures are best way to appliances. This paper presents novel method recognizing hand smart using imaging sensors. The proposed model divided into six steps. First, preprocessing done de-noise video frames resize each frame specific dimension. Second, detected single shot detector-based...