Background Wearable sensing and information communication technologies are key enablers driving the transformation of health care delivery toward a new model connected (CH) care. The advances in wearable last decade evidenced plethora original articles, patent documentation, focused systematic reviews. Although technological innovations continuously respond to emerging challenges technology availability further supports evolution CH solutions, widespread adoption wearables remains hindered....

The Internet of things (IoT) has emerged as a topic intense interest among the research and industrial community it had revolutionary impact on human life. rapid growth IoT technology revolutionized life by inaugurating concept smart devices, healthcare, industry, city, grid, others. devices’ security become serious concern nowadays, especially for healthcare domain, where recent attacks exposed damaging vulnerabilities. Traditional network solutions are well established. However, due to...

Ambient-assisted living (AAL) is promising to become a supplement of the current care models, providing enhanced experience people within context-aware homes and smart environments. Activity recognition based on sensory data in AAL systems an important task because 1) it can be used for estimation levels physical activity, 2) lead detecting changes daily patterns that may indicate emerging medical condition, or 3) detection accidents emergencies. To accepted, must affordable while reliable...

Scene classification relying on images is essential in many systems and applications related to remote sensing. The scientific interest scene from remotely collected increasing, datasets algorithms are being developed. introduction of convolutional neural networks (CNN) other deep learning techniques contributed vast improvements the accuracy image such systems. To classify areal images, we used a two-stream architecture. We performed first part classification, feature extraction, using...

Air pollution is becoming a rising and serious environmental problem, especially in urban areas affected by an increasing migration rate. The large availability of sensor data enables the adoption analytical tools to provide decision support capabilities. Employing sensors facilitates air monitoring, but lack predictive capability limits such systems’ potential practical scenarios. On other hand, forecasting methods offer opportunity predict future specific areas, potentially suggesting...

Background Ambient assisted living (AAL) is a common name for various artificial intelligence (AI)—infused applications and platforms that support their users in need multiple activities, from health to daily living. These systems use different approaches learn about make automated decisions, known as AI models, personalizing services increasing outcomes. Given the numerous developed deployed people with needs, conditions, dispositions toward technology, it critical obtain clear...

Large-scale labeled datasets are generally necessary for successfully training a deep neural network in the computer vision domain. In order to avoid costly and tedious work of manually annotating image datasets, self-supervised learning methods have been proposed learn general visual features automatically. this paper, we first focus on colorization with generative adversarial networks (GANs) because their ability generate most realistic results. Then, via transfer learning, use as proxy...

In today’s urban environments, accurately measuring and forecasting air pollution is crucial for combating the effects of pollution. Machine learning (ML) now a go-to method making detailed predictions about levels in cities. this study, we dive into how settings measured predicted. Using PRISMA methodology, chose relevant studies from well-known databases such as PubMed, Springer, IEEE, MDPI, Elsevier. We then looked closely at these papers to see they use ML algorithms, models, statistical...

One class of applications for human activity recognition methods is found in mobile devices monitoring older adults and people with special needs. Recently, many studies were performed to create intelligent the activities. However, different market acquire data from sensors at frequencies. This paper focuses on implementing four normalization techniques, i.e., MaxAbsScaler, MinMaxScaler, RobustScaler, Z-Score. Subsequently, we evaluate impact algorithms deep neural networks (DNN)...

The application of pattern recognition techniques to data collected from accelerometers available in off-the-shelf devices, such as smartphones, allows for the automatic activities daily living (ADLs). This can be used later create systems that monitor behaviors their users. main contribution this paper is use artificial neural networks (ANN) ADLs with acquired sensors mobile devices. Firstly, before ANN training, device collection. After devices are apply an previously trained ADLs’...

Remote Sensing (RS) image classification has recently attracted great attention for its application in different tasks, including environmental monitoring, battlefield surveillance, and geospatial object detection. The best practices these tasks often involve transfer learning from pre-trained Convolutional Neural Networks (CNNs). A common approach the literature is employing CNNs feature extraction, subsequently train classifiers exploiting such features. In this paper, we propose adoption...

Air pollution is a global problem, especially in urban areas where the population density very high due to diverse pollutant sources such as vehicles, industrial plants, buildings, and waste. North Macedonia, developing country, has serious problem with air pollution. The highly present its capital city, Skopje, places it consistently within top 10 cities world during winter months. In this work, we propose using Recurrent Neural Network (RNN) models long short-term memory units predict...

Connected health is expected to introduce an improvement in providing healthcare and doctor-patient communication while at the same time reducing cost. would even more significant gap between quality for urban areas with physical proximity better providers portion of rural numerous connectivity issues. We identify these challenges using user scenarios propose LoRa based architecture addressing challenges. focus on energy management battery-powered, affordable IoT devices long-term operation,...