In the agricultural domain, the main challenge is to present the new information and research to the farmers so that they can leverage the power of ICT to improve their agricultural practices and thereby the production. Huge amount of agriculture related data like weather data, soil health records, cropping pattern, location specific crop disease and pest are collected from different sources like services, remote satellites, and network of sensors. An agro advisory system presented in this paper helps to bridge the gap between farmers and the agriculture domain experts and developed for the cotton farmers in Gujarat region of India. The system consists of three basic components; Cotton Ontology, Web Services, and Mobile Application Development. The cotton ontology maintains domain knowledge required for answering farmer queries. The ontology contains information regarding crop, soil, cultivation process, disease, pest, and other relevant information. Protege ontology development tool is used to develop this ontology. Appropriate web services were built which help interactions with different data sources. The RESTful web services are programmed in Java using the JAX-RS/Jersey API and the Eclipse EE IDE. The services are developed and deployed on a cloud based application server provided by Heroku. The web services are invoked from the mobile device and in turn they connect to various data sources like Open Weather API, SQL database and the Ontologies. The farmers can use this application based on very simple android mobile interfaces. The prototype is developed using Java, Android SDK -v14 and Eclipse IDE.
Internet of Things is projected to connect uniquely identifiable devices over the network to build an interactive system with high velocity and volume of data placing forth a challenge of interoperability between such devices. RDF provides a common standard for communication among devices of network and supports powerful data inference. The paper addresses the challenge of handling huge sensor data interactively using RDF. The experiment includes various RDF storage mechanisms such as triple store, property table, vertically and horizontally partitioned table, column store, and data aware hybrid storage. It also shows comparison between vertical partitioning approach and data aware hybrid storage approach for faster data retrieval in IOT systems. The experiment shows 12% of performance improvement using hybrid approach over vertical partitioning approach. It also represents a set of metrics which have been designed to take decision for using appropriate RDF data storage technique beforehand for IOT systems.
Mobile devices are used extensively by the people for communication, music, entertainment, Internet and social networking. There is a lack of applications, which can be really useful for the professionals to improve their working capabilities. Though mobile phones are used by people living in rural areas, but there are hardly any relevant applications for them to improve their productivity. In this paper, we have proposed and implemented an information system for farmers which can be operated on their mobile phones. The system is developed using Service Oriented Architecture (SOA) to process spatial data and knowledge base. The knowledge base is maintained in the form of ontologies. The system is an effort to fill the gap between farmers and agricultural experts. A farmer can provide inputs related to crops being cultivated and location specific information to get specific suggestions, alerts and recommendations to improve productivity. It will be generated using the knowledge base. Whenever a farmer observes some anomalous behavior for crops or climate, the system is able to generate recommendations based on inputs provided. We have resolved some of the queries as a part of on-going work and results are displayed on an Android based mobile devices for demonstration of the system.
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