Modern trends in agriculture with wire less sensor networks and Mobile Computing By Dr Lakshman Rao ( Prakasam Engineering College ), G V S N R V Prasad ( Gudlavalleru Engineer College )

Objective Empower farmers with real time decision making for farming using Mobile Phones and information processing through cloud infrastructure. Detailed analysis will be done through regression analysis and analyzed through forecasting techniques which is helpful for better yielding of crops and support by having dedicated agriculture mobile computing lab. The focus areas are, 1.Agricultural, Fish & Prawn Ponds 2.Environment 3.Disaster management 4.Energy-sustainability

Layer 1: Monitoring various parameters at farming land by using Mobile network sensors Mobile phones can be used for observing some agriculture field parameters through image processing with some customization and we have to design some special sensors as plug-in to mobile phone for remaining parameters. Following are the parameters to be monitored by farmer in general, 1.Temperature 2.Humidity 3.Soil Moisture 4.Wind speed, direction 5.Rain Fall 6.Sunshine 7.CO 2, etc

Layer 2: Processing monitored parameters via cloud servers Mobile app uses GPRS or wireless network to communicate monitored parameters to cloud server. Cloud server application processes all the parameters against the semantic decision making system on cloud server and then constructs the recommend the follow up action for farmer. The constituents of semantic decision making system are as follows, 1.Data store and data mining tools & techniques 2.Forecasting techniques 3.Mathematical modeling 4.History, trend generations 5.Local language conversion and visual presentation 6.Optimized network content delivery

Layer 3: Deliver right decisions back to farmers through mobile phone in local language Local language mobile app receives decisions from the cloud server app as push notification converted in local language and local app displays the same either in visual or textual format (based on farmer’s network bandwidth) for farmer to understand easier. Local app also will have cache storage on mobile for farmer to access even when not in network as history of his field.

Future Scope The same system can be enhanced for the following concepts as well 1.AI Pattern based decisions on the server 2.Mobile phone based tractor cultivation 3.Connecting supply of crop yielding to Govt, Buying vendors for better decision making on quality and pricing parts