Invited Talk IoT Cloud-based Services for a Safer Home Automated System

摘要

Nowadays, urban areas have a high density of houses per square kilometer. Any home incident can provoke a great disaster in residential areas. This will cause a serious issue in terms of victims and properties damage. A more efficient and global solution for preventing such disasters in houses is required to improve the existing systems. Opportunely, with the drastic penetration of low-cost embedded and Internet-of-Things (IoT) devices and the big potential of the paradigm Cloud-as-a-Service (CaaS), this can leverage the previous issues to prevent many incidences. In this paper, we propose an alternative method that explores Machine Learning (ML) capabilities in cloud to build up our cost-effective system for gathering the pertaining information that causes disasters in residence areas. The proposed system can track the abnormal air conditioning changes from hidden patterns that might cause problems. The system developed would be able to generate real-time forecasts, inform and advise the situation to the relevant persons in time, and initiate a procedural plan in case of emergency. This research is conducted to make homes safer and protect people's most important assets.