Interesting

 Primarily, precision farming involves the measurement and understanding of variability over time and space. This system is based on use of information generated through surveys to manage this variability by matching inputs to conditions within fields using site-specific inputs. Finally, and most important, this system provide for the measurement and recording of the efficiency of these site-specific practices in order to assess value on and off the farm. The precision farming system is information based and technology enabled, is thus efficient.  But the question raised is pertinent that how to improve information sharing on farm. There is need to work out open data models for different locations and situations. acceptable to all stakeholders ICT producers, hardware producers, service organization and others. Compliments to Karel Charvat in this endeavour.

We would like establish broader cooperation in this area with both private and public sector. We see that ne PF technologies will be better adopted by farmers, if there will be possible easy combine technologies form different providers

Yes, we can improve sharing and exchange of information on farm as long as we use existing standards for the recording, aggregation and sharing of farm data instead of proprietary ones. In my opinion, the current issue related to the lack of interoperability between different farm management tools/platforms is the use of proprietary standards that create data silos and bound farmers with specific software and hardware.

The future lies in open data and sharing; the sooner the companies realize it, the better it is.

By the way, another interesting initiative is the Open Ag Data Alliance (http://openag.io/), which may also be a part of the Ag Data Coalition (through Purdue University); they are doing a great job in terms of ag data interoperability and security.

Dear Vassilis, we need some umbrela, which will help to join single innitiatives. This is only chance to succed. Some years I hope, that such group coub be under EFITA for example, but it was not succesfull.  We need look on some existing innitiative to join people

Migaly, it is true, that interoperability in public sector is bich challange. We have for example INSPIRE for spatial data, but it is not helping to much to famers

You can see the experience of Agropedia http://agropedia.iitk.ac.in

It is good, but will be good to discussed standards for exchange of information and knowledge

The most common technologies applied to Precision Farming practices and this is a knowledge based technique, the following component are very much essential for precision farming:

 1.     High precision positioning systems (like GPS) are the key technology to achieve accuracy when driving in the field, providing navigation and positioning capability anywhere on earth, anytime under any all conditions. The systems record the position of the field using geographic coordinates (latitude and longitude) and locate and navigate agricultural vehicles within a field with 2cm accuracy.

 2.      Automated steering systems: enable to take over specific driving tasks like auto steering,

overhead turning, following field edges and overlapping of rows. These technologies reduce human error and are the key to effective site management:  Assisted steering systems show drivers the way to follow in the field with the help of satellite navigation systems such as GPS. This allows more accurate driving but the farmer still needs to steer the wheel. Automated steering systems, take full control of the steering wheel allowing the driver to take the hands off the wheel during trips down the row and the ability to keep an eye on the planter, sprayer or other equipment. Intelligent guidance systems provide different steering patterns (guidance patterns) depending on the shape of the field and can be used in combination with above systems.

 3.     Geomapping: used to produce maps including soil type, nutrients levels etc in layers and assign that information to the particular field location.

4.     Sensors and remote sensing: collect data from a distance to evaluating soil and crop health (moisture, nutrients, compaction, crop diseases). Data sensors can be mounted on moving machines.

5.     Integrated electronic communications between components in a system for example, between tractor and farm office, tractor and dealer or spray can and sprayer. Caption: Seeder using a geomapping system

6.     Variable rate technology (VRT): ability to adapt parameters on a machine to apply, for instance, seed or fertilizer.

What about Yiled monitoring (from havestors) or Yiled prediction from satellites

@Karel: INSPIRE is a great example of an umbrella initiative for joining data-related initiatives in another context. Maybe GODAN / one of the Working Groups of GODAN (http://www.godan.info/working-groups-list) or the RDA agricultural data interoperability groups (https://www.rd-alliance.org/groups/agriculture-data-interest-group-igad.html) could play this role for agricultural / smart farming data.

In both cases, we may have the opportunity to intervene and describe our concept so that we can raise interest among existing participants and communities.

Thanks, it good to disussed it. We are now planning to publish our FOODIE data model on GitHub, to have chance better discussed it with others

 Dear Mr. Karel. Good discussion on the topic. With the revolution in information technology, now it has become possible to focus on the positioning of agricultural tools with high degree of accuracy and sophistication for maximizing returns. The combination of information technology and use of hi-tech equipments made it possible for the introduction of precision farming.  It is a comprehensive system designed to optimize agriculture production through the application of crop information, advanced technology and management practices. With recent advances in geographic information systems, it has become possible to focus on site specific crop production technologies so as to harness the potential of agriculture through innovative technologies in a sustainable manner. 

Dear Suresh, it is true. But main problem with this is interoperability

As our contribution to standardisation in agriculture we publish today FOODIE data model on GitHub.  https://github.com/Wirelessinfo/FOODIE-data-model.  We would like invite you discussed and improved with us this model. FOODIE data model is available under Attribution-ShareAlike 4.0 International licence.

See next presentation as explanation of FOODIE data model.

PostgreSQL script for FOODIE data model. See https://github.com/Wirelessinfo/FOODIE-data-model/commit/dd24205d7ed8646d1c997b482b5b1e8b270b00db

Added PostgreSQL script creating schema, tables and relations between

tables. This script creates one of many possible sql representations of

FOODIE data model. Selected approach will be explained in next update.