COSMOS has released the final version of the project newsletter, covering advancements from January 2016 to August 2016, including project's outcomes, use cases demonstration, publications drafting, events attendance and events organisation.
The main goal of this scenario is to improve user experience of passengers with special needs (SP) and their caregivers (CG). Passengers such as children, elderly, disabled and the like, may choose to use the bus system if they can get assistance on the beginning and end of their journey.
The Hardware Security Board consists of a physical hardware device which provides the link between sensors (data generators) and the COSMOS environment/platform. The Hardware Security Board can be either attached to one sensor or can be a hub for an entire collection of sensors (e.g. temperature, pressure, humidity, surveillance cameras, etc.).
Inference and Prediction functional component is responsible for providing high-level knowledge from raw IoT data using different pattern recognition techniques. In this context, we have explored several supervised machine learning techniques including different variants of Support Vector Machines and K- Nearest Neighbor, in addition to statistical techniques such as Hidden Markov Model (HMM).
Storlets are computational objects that run inside the object store system. Conceptually, they can be thought of the object store equivalent of database store procedures. The basic idea behind storlets of performing the computation near the storage is saving on the network bandwidth required to bring the data to the computation.
The Data Mapper functional component is responsible for the ingestion of IoT data flowing on the COSMOS Message Bus into the cloud storage, annotating them with enriching metadata.
