Abstract
By a News Reporter-Staff News Editor at Robotics & Machine Learning Daily News Daily News – New study results on artificial intelligence have been published. According to news reporting originating from Islamabad, Pakistan, by NewsRx correspondents, research stated, “Smartwatches with cutting-edge sensors are becoming commonplace in our daily lives.” Funders for this research include Deanship of Scientific Research At Jouf University; Eu Nextgenera- tioneu Through The Recovery And Resilience Plan For Slovakia. The news journalists obtained a quote from the research from COMSATS University Islamabad: “De- spite their widespread use, it can be challenging to interpret accelerometer and gyroscope data efficiently for Human Activity Recognition (HAR). This study explores active learning integrated with machine learn- ing, intending to maximize the use of smartwatch technology across a range of applications. The previous research on the HAR lacks promising performance, which could make it difficult to make highly accurate recognition. This paper proposes a novel approach to predict human activity from the Heterogeneity Hu- man Activity Recognition (HHAR) dataset that integrates active learning with machine learning models: Random Forest (RF), Extreme Gradient Boosting (XGBoost), K-nearest Neighbors (KNN), Decision Tree (DT), Gradient Boosting (GB) and Light Gradient Boosting Machine (LGBM) classifier to predict hetero- geneous activities accurately. We evaluated our approach to these models on the HHAR dataset that was generated using an accelerometer and gyroscope of smartwatches. The experiments are evaluated on 3 iterations where the results demonstrated that the proposed approach predicts human activities with the highest F1-Score of 99.99%.”
NETL
NSTL
IEEE