Coronavirus disease (COVID-19) is a pandemic disease, which has already caused thousands of causalities and infected several millions people worldwide. Any technological tool enabling rapid screening the COVID-19 infection with high accuracy can be crucially helpful to healthcare professionals. The main clinical currently in use for diagnosis Reverse transcription polymerase chain reaction (RT-PCR), expensive, less-sensitive requires specialized medical personnel. X-ray imaging an easily...

Tuberculosis (TB) is a chronic lung disease that occurs due to bacterial infection and one of the top 10 leading causes death. Accurate early detection TB very important, otherwise, it could be life-threatening. In this work, we have detected reliably from chest X-ray images using image pre-processing, data augmentation, segmentation, deep-learning classification techniques. Several public databases were used create database 3500 infected normal for study. Nine different deep CNNs (ResNet18,...

Plants are a major source of food for the world population. Plant diseases contribute to production loss, which can be tackled with continuous monitoring. Manual plant disease monitoring is both laborious and error-prone. Early detection using computer vision artificial intelligence (AI) help reduce adverse effects also overcome shortcomings human In this work, we propose use deep learning architecture based on recent convolutional neural network called EfficientNet 18,161 plain segmented...

Hypertension is a potentially unsafe health ailment, which can be indicated directly from the Blood pressure (BP). always leads to other complications. Continuous monitoring of BP very important; however, cuff-based measurements are discrete and uncomfortable user. To address this need, cuff-less, continuous non-invasive measurement system proposed using Photoplethysmogram (PPG) signal demographic features machine learning (ML) algorithms. PPG signals were acquired 219 subjects, undergo...

Traditional waste management system operates based on daily schedule which is highly inefficient and costly. The existing recycle bin has also proved its ineffectiveness in the public as people do not their properly. With development of Internet Things (IoT) Artificial Intelligence (AI), traditional can be replaced with smart sensors embedded into to perform real time monitoring allow for better management. aim this research develop a using LoRa communication protocol TensorFlow deep...

The immense spread of coronavirus disease 2019 (COVID-19) has left healthcare systems incapable to diagnose and test patients at the required rate. Given effects COVID-19 on pulmonary tissues, chest radiographic imaging become a necessity for screening monitoring disease. Numerous studies have proposed Deep Learning approaches automatic diagnosis COVID-19. Although these methods achieved outstanding performance in detection, they used limited X-ray (CXR) repositories evaluation, usually with...

Photovoltaics (PV) output power is highly sensitive to many environmental parameters and the produced by PV systems significantly affected harsh environments. The annual density of around 2000 kWh/m2 in Arabian Peninsula an exploitable wealth energy source. These countries plan increase contribution from renewable (RE) over years. Due its abundance, focus RE on solar energy. Evaluation analysis performance terms predicting with less error demands investigation effects relevant performance....

Detecting COVID-19 at an early stage is essential to reduce the mortality risk of patients. In this study, a cascaded system proposed segment lung, detect, localize, and quantify infections from computed tomography images. An extensive set experiments were performed using Encoder–Decoder Convolutional Neural Networks (ED-CNNs), UNet, Feature Pyramid Network (FPN), with different backbone (encoder) structures variants DenseNet ResNet. The conducted for lung region segmentation showed Dice...

Coronavirus disease (COVID-19) has been the main agenda of whole world ever since it came into sight. X-ray imaging is a common and easily accessible tool that great potential for COVID-19 diagnosis prognosis. Deep learning techniques can generally provide state-of-the-art performance in many classification tasks when trained properly over large data sets. However, scarcity be crucial obstacle using them detection. Alternative approaches such as representation-based [collaborative or sparse...

Diabetes foot ulceration (DFU) and amputation are a cause of significant morbidity. The prevention DFU may be achieved by the identification patients at risk institution preventative measures through education offloading. Several studies have reported that thermogram images help to detect an increase in plantar temperature prior DFU. However, distribution heterogeneous, making it difficult quantify utilize predict outcomes. We compared machine learning-based scoring technique with feature...

Abstract The reliable and rapid identification of the COVID-19 has become crucial to prevent spread disease, ease lockdown restrictions reduce pressure on public health infrastructures. Recently, several methods techniques have been proposed detect SARS-CoV-2 virus using different images data. However, this is first study that will explore possibility deep convolutional neural network (CNN) models from electrocardiogram (ECG) trace images. In work, other cardiovascular diseases (CVDs) were...

Cardiovascular diseases are one of the most severe causes mortality, annually taking a heavy toll on lives worldwide. Continuous monitoring blood pressure seems to be viable option, but this demands an invasive process, introducing several layers complexities and reliability concerns due non-invasive techniques not being accurate. This motivates us develop method estimate continuous arterial (ABP) waveform through approach using Photoplethysmogram (PPG) signals. We explore advantage deep...

One of the major causes death all over world is heart disease or cardiac dysfunction. These diseases could be identified easily with variations in sound produced due to activity. sophisticated auscultations need important clinical experience and concentrated listening skills. Therefore, there an unmet for a portable system early detection illnesses. This paper proposes prototype model smart digital-stethoscope monitor patient's sounds diagnose any abnormality real-time manner. consists two...

Pneumonia is a life-threatening disease, which occurs in the lungs caused by either bacterial or viral infection. It can be life-endangering if not acted upon right time and thus an early diagnosis of pneumonia vital. The aim this paper to automatically detect using digital x-ray images. provides detailed report on advances made making accurate detection then presents methodology adopted authors. Four different pre-trained deep Convolutional Neural Network (CNN)- AlexNet, ResNet18,...

Abstract COVID-19 pandemic has created an extreme pressure on the global healthcare services. Fast, reliable, and early clinical assessment of severity disease can help in allocating prioritizing resources to reduce mortality. In order study important blood biomarkers for predicting mortality, a retrospective was conducted dataset made public by Yan et al. [1] 375 positive patients admitted Tongji Hospital (China) from January 10 February 18, 2020. Demographic characteristics patient...

Heart attack is one of the leading causes human death worldwide. Every year, about 610,000 people die heart in United States alone-that every four deaths-but there are well understood early symptoms that could be used to greatly help saving many lives and minimizing damages by detecting reporting at an stage. On other hand, 2.35 million get injured or disabled from road accidents. Unexpectedly, these fatal accidents happen due drivers leads loss control vehicle. The current work proposes...

Gait analysis is a systematic study of human locomotion, which can be utilized in variousapplications, such as rehabilitation, clinical diagnostics and sports activities. The various limitationssuch cost, non-portability, long setup time, post-processing time etc., the current gait analysistechniques have made them unfeasible for individual use. This led to an increase research interestin developing smart insoles where wearable sensors employed detect vertical groundreaction forces (vGRF)...

Computer-aided diagnosis has become a necessity for accurate and immediate coronavirus disease 2019 (COVID-19) detection to aid treatment prevent the spread of virus. Numerous studies have proposed use Deep Learning techniques COVID-19 diagnosis. However, they used very limited chest X-ray (CXR) image repositories evaluation with small number, few hundreds, samples. Moreover, these methods can neither localize nor grade severity infection. For this purpose, recent explore activation maps...

Growing plants in the gulf region can be challenging as it is mostly desert, and climate dry. A few species of have capability to grow such a climate. However, those are not suitable food source. The aim this work design construct an indoor automatic vertical hydroponic system that does depend on outside designed capable common type crops used source inside homes without need large space. was made after studying different types systems terms price, power consumption suitability built...

Optical wavelengths considered as the key source of electromagnetic waves from sun, and metamaterial absorber (MMA) enables various applications for this region like real invisible cloaks, color imaging, magnetic resonance light trapping, plasmonic sensor, detector, thermal imaging applications. Contemplated those applications, a new wide-angle, polarization-insensitive MMA is presented in study. The was formatted with three layers that consisted sandwiched metal-dielectric-metal structure....