Before attempting anything to present or comment anything for the topic, it is imperative that we take a look at the broader picture. One of the broad consensus is that, by 2050 the world population is going to be around 9.6 billion. A large chunk of the population will be employed by non-agricultural sectors especially services. This has huge implications for agricultural production and distribution. The important reason is that the inputs for agricultural production are going to reduce significantly, especially water and on the other hand we have to feed 9.6 billion, with the verities of grain they consume and agricultural produce they consume.
The Indian Scene
During the years 1993-1994 & 2009-2010 the employment declined from 78.43% to 67.96% while agricultural wage rate increased by 2.69% in real terms as compared to 1.75% in the non-agricultural sector. The ultimate objective of this statistics is that the most important cost element of agriculture – labour is not only getting dearer but is just evaporating in the non-agricultural sectors. In conclusion, the future agriculture has to depend on smarter machines.
Mechanisation of Agriculture:
Tractors for sowing of seeds and sapling at centimeter distance are available. So, the mechanical implements take care of the labour intensive part. The next level is monitoring observations and reactive procedures.
Drones in Agriculture
In the conventional agricultural model, the plant inspection is done manually. Scientific inspection is done for academic purposes. Now agricultural drones will make the observation possible. The drones will be primarily used for:
- Soil Analysis
- Crop Spraying
- Crop Monitoring
- Irrigation (Hyperspectral, multispectral, thermal, recognise which parts of the fields are dry and which need to be irrigated.
- Health Assessments (Tracking, bacterial or fungal infections, on trees)
The Possible benefits are
- Helps in new ways to increase yields and reduce crop damage.
- Relatively cheap drones with advanced sensors. Sensors can monitor chlorophyll levels.
- Cost of 1 hour of aerial photography is $1000 and a drone can be bought for $1000.
- This is possible because of cheap MEMS sensors small GPS modules incredibly powerful processors, pressure sensors, need good visual spectrum
- Drone survey can cover the crop survey daily weekly and monthly and create a time series.
- Data driven agriculture
- Farms are bursting with automation technology with tractors planting seeds every centimetre. What this all means is reducing the risk of a final crop due to various adverse factors. Extensive wireless network data backhaul data on soil and hydration environmental conditions.
Programming for Drones
Though the hardware is promising but without the software the drone would be a sitting machine doing nothing worthwhile. To This end we build application programming interfaces for:
- Brushless DC motors
- Electronic speed controllers (ESCs)
- Power supply board
- Radio Control
- Control Board sensors (Transmitters and receivers)
- Control Board sensors and GPS
- Lipo Battery
We use some of the current languages for drone programming which are Java API for drones, C#.NET, Python Air Drone, AR drone Auto Pylot, Auto Pilot Drone API, Ruby: Adaptor for, AR Drone., Argus, Ruby tool box. It is important to realize that the video editor has to be robust. It should be able to capture the best parts of the flight.
The story just doesn’t end with the high-resolution image capturing the field data has to be sent to the agronomists who can tell the plant indicators. The data can be monitored for daily weekly and monthly basis and create a time-line data for the growing crops.
Our endeavour in this field is a beginning but the costs for the drones are encouraging. It costs anywhere between Rs1500 to Rs 7 lacs for a drone. The only drag could be the government regulations.