Strategic directions in database systems—breaking out of the box
ACM Computing Surveys (CSUR) - Special ACM 50th-anniversary issue: strategic directions in computing research
Designing interactive information access technologies for small scale rural indian farmers
CHI '09 Extended Abstracts on Human Factors in Computing Systems
Understanding the dynamics of crop problems by analyzing farm advisory data in eSagu™
DNIS'07 Proceedings of the 5th international conference on Databases in networked information systems
FOLKSOMAPS - towards community driven intelligent maps for developing regions
ICTD'09 Proceedings of the 3rd international conference on Information and communication technologies and development
International Journal of Computational Science and Engineering
Interface tailoring by exploiting temporality of attributes for small screens
DNIS'10 Proceedings of the 6th international conference on Databases in Networked Information Systems
Temporality-based user interface design approaches for desktop and small screen environment
International Journal of Computational Science and Engineering
IHCI'10 Proceedings of the 2010 international conference on Interaction Design & International Development
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In this paper, we explain a personalized agricultural advisory system called eSagu, which has been developed to improve the performance and utilization of agriculture technology and help Indian farmers. In eSagu, rather than visiting the crop in person, the agricultural expert delivers the expert advice at regular intervals (once in one or two weeks) to each farm by getting the crop status in the form of digital photographs and other information. During 2004-06, through eSagu, agricultural expert advices delivered for about 6000 farms covering six crops. The results show that the expert advices helped the farmers to achieve savings in capital investment and improved the crop yield. Mainly, the data warehouse of farm histories has been developed which is providing the crop related information to the agricultural expert in an integrated manner for generating a quality agricultural expert advice. In this paper, after explaining eSagu and its advantages, we discuss how data warehouse of farm histories is enabling agricultural expert to deliver a quality expert advice. We also discuss some research issues to improve the performance of eSagu.