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In July 2018, the Karnataka Government launched a Centre of Excellence in Data Sciences and Artificial Intelligence in collaboration with NASSCOM. The CoE initiative is a nationwide program on innovative solutions in smart manufacturing, automotive, healthcare, agriculture, energy, IoT, retail, telecom, banking, and financial services.
In October 2017, the Government of Karnataka signed a MoU with Microsoft India to increase farmers’ income using cloud-based technologies, machine learning, and advanced analytics. The MoU will help Karnataka Agricultural Price Commission (KAPC) and Department of Agriculture to improve price forecasting model based on various datasets such as historical sowing area, production, yield, and weather. The MoU aims to bring digital farming using Microsoft Cortana Intelligence Suite including technologies such as machine learning and business intelligence.
The primary source of revenue for Karnataka Forest Department is sale of timber. Currently there is no predictability on the expected baselines and revenues. Also, there are no Level-1 insights generated pre/post the sale process. This leads to lost opportunities in maximizing revenues leading to a better process of KFD in meeting their objective of a “Better Forest”.
KFD and Nasscom CoE ran workshops, competition and hackathons with 60+ shortlisted B-Tech Start-ups and AI innovators from across Karnataka to identify and finalize 1 AI machine learning analytics vendors with custom solution with 5 years historic data on 1,400 registered bulk purchasers, which include sawmills and companies. Nine lakh tons of lots of timber sales data from 2013 to December 1, 2018 was analysed, churned and deep learning algorithm deployed to identify the following
Timeline: 6 to 9 months
KSPCB is responsible to monitor, prevent, control & abatement of pollution across State. Monitoring done by multiple vendors using different systems. Each vendor gives data in different formats and visualizations and inconsistent reporting schedules.
Their main objectives are:
i. Pin Code or Area Wise Level of Air Pollution
ii. Pin Code or Area Wise Weather Conditions
iii.Type of reporting visualizations
iv. Type of reporting schedules
v. Correlation of Pollution, Weather Conditions, Moisture, # of Cars, # of Factories and commercial establishments to understand air pollution levels.
1. By Type of Transactions
2. By Type of Wood
3. By GEO/Warehouse or Bidding location
vi. Behaviour of non-pollutants
vii. Behaviour of pollutants
viii. Best Air Quality time by Area/Pin Code
ix. Worst Air Quality time by Area/Pin Code
“INTELLIGENT VISUALIZATION” for Ambient Air Monitoring was designed and delivered by KSPCB making it first of its kind by a state government.
Timeline: 8 to 10 months