iSSEE: IMS Sensors Search Engine Enabler for Sensors Mashups Convergent Application
Abdelkader Outtagarts, Olivier Martinot

TL;DR
The paper introduces iSSEE, a search engine enabler for IMS sensors that facilitates dynamic discovery of sensor status, location, and type, enabling innovative multimedia mash-up applications over IP networks.
Contribution
It presents the design and implementation of iSSEE, a novel application enabler that enhances sensor discovery and data integration for IMS-based multimedia applications.
Findings
iSSEE effectively provides real-time sensor availability and location information.
The system supports diverse sensor types for multimedia mash-ups.
Enables dynamic, convergent applications using heterogeneous sensor data.
Abstract
Integrating the sensing capabilities in Internet Protocol network will open the opportunities to build a wide range of novel multimedia applications. The problem when using sensors (e.g. temperature sensor, camera, audio, humidity, etc.) connected to the network is to know dynamically at any time if they are always connected or not, what type of data they can transmit and where they are geographically located. This paper describes an application enabler: IMS Sensor Search Engine Enabler (iSSEE), which allows IMS applications using sensors and IMS based devices, to get information about the sensor availability, its location and the type of the sensor. Using data collected by sensors and from the web, mash-ups convergent applications use cases are proposed by combining the contents from heterogeneous data.
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsVideo Analysis and Summarization · Multimedia Communication and Technology · Caching and Content Delivery
