AI in Agricultural & Healthcare-Smart Farming Using Artificial, Drones & Remote Sensing

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In Andhra Pradesh՚s Devanakonda Mandal in Kurnool district where farmers depended on rain for groundnut and cotton crops now use AI to get accurate predictions. With landholdings of just two to three acres and poor weather prediction most depended on experience to decide when to sow.

AI in Agricultural
  • International Crops Research Institute for Semi-Arid Tropics (ICRISAT) , the Andhra Pradesh government and Microsoft added AI (Artificial Intelligence) .
  • Microsoft Azure cloud platform studied 40 years of data on weather patterns, soil conditions for building a modelling framework with ICRISAT and applied machine learning technologies.
  • Based on advice from AI, they sent correct SMS advisories on sowing to farmers- SMS alerts proved their worth when it rained in May.
  • Those who went by “Expert” advice saw an average 30 % higher yield than those who sowed early

Role of New Technologies- ICRISAT

  • Cloud computing, machine learning, artificial intelligence technologies, powerful communication and collaboration tools enable gathering and analyzing large volumes of data to take future decisions.
  • Potential applications are in education, healthcare, industry and agriculture- potential to transform lives.
  • ICRISAT program has been expanded to cotton, ragi, rice, and maize in 13 districts of AP.

Price Forecasting Using AI

  • ICRISAT and Microsoft entered an understanding with Karnataka to develop an agricultural commodity price-forecasting model for “tur” crop.
  • The program reaches 2,500 farmers in Andhra, and 1,200 in Karnataka with plans to reach 10,000 farmers in each state
  • A senior Cisco executive notes that two-thirds of the population is in rural areas, but two thirds of our resources are in urban areas. “New technologies are enabling the transfer of the latter strengths to the former,” he says.

Other Agricultural Technological Interventions

  • IIT-Madras uses drones to do multispectral aerial imaging of plant leaves to understand the health of a crop, and advises farmers on what NPK (nitrogen, phosphorus, potassium) fertilizer ratio to use.
  • A new firm has established “Uber” for tractors- only 10 % of the country՚s farmers can afford farm machinery so the shared agricultural equipment model provides farm machinery and vehicles on demand. Technology allows speedy service and transparent billing.

Healthcare Technological Interventions

  • In healthcare, technology is useful where doctors are hard to reach.
  • For example, thermal images and artificial intelligence can be used assess energy level in cells and detect breast cancer remotely and at lower costs.
  • Bengaluru-based SigTuple uses a small camera to read pathology samples and send the data to a cloud server that analyses and produces a digital report instantly.

Telecommunication Transforming Remote Education and Healthcare

  • Cisco adopted five villages in Raichur district, rebuilt over 3,000 homes, and established four networked schools and a digital healthcare centre.
  • Teachers in Bengaluru delivered live video courses over the internet in English, mathematics, science, and social science to 1,000 children in the newly equipped schools.
  • The healthcare centre enabled live remote consultations with doctors in Bengaluru.

AI Used for Detecting Cancer

  • New research from Japanese scientists suggests AI could be used to detect colorectal cancer in its earliest stages, before tumors become malignant and the deadly cancer becomes much harder to treat with 86 % accuracy.
  • Study lead Dr. Yuichi Mori of Showa University collected tens of thousands of high-resolution images of pre-cancerous and cancerous cells in order to kick the machine learning process into gear
  • After training, the AI algorithm was able to discern cancers from highly magnified pictures of colorectal polyps within just a second.
  • Colorectal cancer can become deadly as it can easily spread to the lymph nodes or blood stream.
  • AI has also been tested in reading X-rays and brain scans and even narrowing down the list of possible genetic diseases a patient suffers simply by analyzing his or her face.

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