Smart Laptop Bag with Machine Learning for Activity Recognition
This addresses the problem of real-time tracking and health monitoring for tech-savvy users, but it is incremental as it applies existing machine learning methods to a new device.
The paper tackles the problem of monitoring personal possessions and user health by developing a smart laptop bag that integrates location tracking, ambiance monitoring, and user-state monitoring, achieving over 95% accuracy in experimental results using deep neural networks.
In todays world of smart living, the smart laptop bag, presented in this paper, provides a better solution to keep track of our precious possessions and monitoring them in real time. As the world moves towards a much tech-savvy direction, the novel laptop bag discussed here facilitates the user to perform location tracking, ambiance monitoring, user-state monitoring etc. in one device. The innovative design uses cloud computing and machine learning algorithms to monitor the health of the user and many parameters of the bag. The emergency alert system in this bag could be trained to send appropriate notifications to emergency contacts of the user, in case of abnormal health conditions or theft of the bag. The experimental smart laptop bag uses deep neural network, which was trained and tested over the various parameters from the bag and produces above 95% accurate results.