Blockchain and IoT integration for secure short-term and long-term air quality monitoring system using optimized neural network.

Accurate air pollution prediction is vital for residents' well-being. This research introduces a secure air quality monitoring system using neural networks and blockchain for robust analysis, precise predictions, and early pollution detection. Blockchain guarantees data integrity, security, and transparency.

HARNet in deep learning approach-a systematic survey.

A comprehensive examination of human action recognition (HAR) methodologies situated at the convergence of deep learning and computer vision is the subject of this article. We examine the progression from handcrafted feature-based approaches to end-to-end learning, with a particular focus on the significance of large-scale datasets. By classifying research paradigms, such as temporal modelling and spatial features, our proposed taxonomy illuminates the merits and drawbacks of each.

A Robust Decision Support System for Wireless Healthcare Based on Hybrid Prediction Algorithm.

Analysis of healthcare data becomes a tedious task as large volume of unlabelled information is generated. In this article, an algorithm is proposed to reduce the complexity involved in analysis of healthcare data. The proposed algorithm predicts the health status of elderly from the data collected at health centres by utilizing PCA (principle component analysis) and SVM (support vector machine) algorithms.