GS (M) Paper-3: “e-technology in the aid of farmers”
GS (M) Paper-3: “Science and Technology- developments and their applications and effects in everyday life”
Big Data For The Next Green Revolution
World is now more inter-connected, spawning massive data and exploration of these data can help to drive decision making that can transform the farm source-to-consumer value chain.
Big Data has the potential to add value across each touchpoints starting from selection of right agri-inputs, monitoring the soil moisture, tracking prices of markets, controlling irrigations, finding the right selling point and getting the right price.
What is Big Data?
Big data is a term that describes a massive volume of both structured and unstructured data that is so large it is difficult to process using traditional database and software techniques.
- The term big data, especially when used by vendors, may refer to the technology (which includes tools and processes) that an organization requires handling the large amounts of data and storage facilities.
- In most enterprise scenarios, the volume of data is too big or it moves too fast or it exceeds current processing capacity. Despite these problems, big data has the potential to help companies improve operations and make faster, more intelligent decisions.
- Banking and retail have been early adopters of Big Data-based strategies. Increasingly, other industries are utilizing Big Data like that from sensors embedded in their products to determine how they are actually used in the real world.
- In healthcare, clinical data can be reviewed treatment decisions based on big data algorithms that work on aggregate individual data sets to detect nuances in subpopulations that are so rare that they are not readily apparent in small samples.
Potentials of big data for the next Green Revolution:
- Big-data businesses can analyse varieties of seeds across numerous fields, soil types, and climates and select the best.
- Similar to the way in which Google can identify flu outbreaks based on where web searches are originating, analysing crops across farms helps identify diseases that could ruin a potential harvest.
- Precision agriculture aids farmers in tailored and effective water management, helping in production, improving economic efficiency and minimising waste and environmental impact.
- Advanced analytics capabilities and agri-robotics such as aerial imagery, sensors help provide sophisticated local weather forecasts can help increasing global agricultural productivity over the next few decades.
- Since, climate change and extreme weather events will demand proactive measures to adapt or develop resiliency, Big Data can bring in the right information to take informed decisions.
- They help in streamlining food processing value chains by finding the core determinants of process performance, and taking action to continually improve the accuracy, quality and yield of production. They also optimise production schedules based on supplier, customer, machine availability and cost constraints.
- In India, every year 21 million tons of wheat is lost, primarily due to scare cold-storage centres and refrigerated vehicles, poor transportation facilities and unreliable electricity supply. Big Data has the potential of systematisation of demand forecasting thus reducing such losses.
- A trading platform for agricultural commodities that links small-scale producers to retailers and bulk purchasers via mobile phone messaging can help send up-to-date market prices via an app or SMS and connect farmers with buyers, offering collective bargaining opportunities for small and marginal farmers.
- The challenges and opportunities of data is immense in a country like India with 638,000 villages and 130 million with 140 million hectares of cultivable land under 127 agro climatic regions capable of supporting 3,000 different crops and one million varieties.
- Self-driven vehicles can already drive themselves across fields using Global Positioning System (GPS) signals accurate to less than inch of error thus helping farmers plant more accurately.
- But the real potential is what happens when this data from thousands of tractors on thousands of farms is collected, grouped and analysed in real time.
- There is need to formulate a business model wherein value can be captured from the scale of data being captured by different players in the agri-supply chain.
- Companies must act now to focus, simplify and standardise big data through an enterprise-wide data management strategy.
India should look at establishing a systematic mechanism to capture the data that could offer additional value-creating opportunities.
It also has the potential to change the agri-business models including revenue models, as businesses will have the opportunity to offer new products and services thus developing sustainable revenue streams.[Ref: Business Line]