Workshop on ‘Data Science for Agriculture and Natural Resource Management' DSANRM 2017

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活动简介

Any kind of development is incomplete without the development in agriculture and in absence of natural resources. What will happen, if we have a developed the society in terms of information and infrastructure but no access to food or natural resources? We are experiencing a tremendous technology growth and evolution of innovative applications using Data Science and Big Data Analytics (BDA). Internet of Agriculture Things (AgThings) helps us to capture big data and in upcoming decade the farms will be a great source of data. The data obtained from farms can be used for precision agriculture and will help farmers or end users to take better decisions. The objective of workshop is to discuss the potential application areas of Data Science in Agriculture and Natural Resource Management domain. This workshop will demonstrate how data integration and analytics using data science can help farmers to increase their earnings and enable them to take better decisions.

The agriculture and natural resource management sector needs keen attention of data science research community for finding innovative solutions to the problem of best utilization of natural resources and to increase the yield of agro-produces. Now a days, we are witnessing the information age and we have best time to make use of available voluminous, dynamic, and real time data for taking most efficient decision for the management of natural resources and agricultural development. The objective of workshop is to provide a platform where researchers, academicians, professionals and practitioners can share state of the art technology for best utilization of natural resources and a highly productive environment for agriculture.

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重要日期

2017-10-16

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征稿范围

The workshop invites original research papers in the areas related to ‘Data Science in Agriculture and Natural Resource Management’. Topics include but are not limited to:

Agricultural Data Model including sensing and reliability
Algorithm Designing and implementation in Agriculture Databases
Big data analytics and social media for agriculture
Cloud and grid computing for agriculture
Data Mining tools for analysis of Spatial Agriculture Data
Data mining with relevance to prognosis of disease
Data mining, graph mining and data science for agriculture
Data science applications in agriculture
Data science for decision support system for natural resource management
Data Warehousing and Integration for Agriculture
Exogenous parameters estimation for increasing crop yield
Framework for mining complex and large data, e.g. a combination of experimentation, images, and use cases
Innovations in agriculture and sensing devices used in farming
Knowledge based agriculture data models
Managing water resources by data analytics
Models and tools for smart computing in agriculture
Online Algorithms and Analytics for data generated by Sensors and Machines used by green houses and precision agriculture
Ontology based study in context to data mining
Precision agriculture and smart farming
Security and privacy for big data in agriculture
Smart devices and hardware for precision agriculture
Smart farming and big data
Smart location-based services for agriculture recommendations
Smart use of natural resources by using data science
Spatial, Temporal and Sequential Agriculture Data Mining
Standards for big data and spatial data in agriculture
Various scalability techniques for processing of large databases
Visualization and analytics of agriculture data