Graphical Query Builder in Opportunistic Sensor Networks to discover Sensor Information

TL;DR

This paper presents a visual query interface for sensor networks that allows users to easily formulate complex queries without prior knowledge of sensor data, translating visual inputs into SPARQL for system processing.

Contribution

It introduces an interactive graphical query builder that simplifies sensor data retrieval by translating visual queries into machine-understandable SPARQL, based on ontology parsing.

Findings

Developed a visual query interface for sensor networks.

Enabled translation of visual queries into SPARQL.

Facilitated user-friendly querying of sensor data.

Abstract

A lot of sensor network applications are data-driven. We believe that query is the most preferred way to discover sensor services. Normally users are unaware of available sensors. Thus users need to pose different types of query over the sensor network to get the desired information. Even users may need to input more complicated queries with higher levels of aggregations, and requires more complex interactions with the system. As the users have no prior knowledge of the sensor data or services our aim is to develop a visual query interface where users can feed more user friendly queries and machine can understand those. In this paper work, we have developed an Interactive visual query interface for the users. To accomplish this we have considered several use cases and we have derived graphical representation of query from their text based format for those use case scenario. We have facilitated the user by extracting class, subclass and properties from Ontology. To do so we have parsed OWL file in the user interface and based upon the parsed information users build visual query. Later on we have translated the visual query languages into SPARQL query, a machine understandable format which helps the machine to communicate with the underlying technology.