Revolutionizing Farming with Data Analytics (1).pdf
- 1. REVOLUTIONIZING FARMING WITH DATA ANALYTICS Transforming Agriculture with Precision, Insights, and Technology @IABAC.ORG
- 2. WHAT IS URBAN FARMING? Growing food in cities using innovative methods What is Traditional Farming? Traditional farming refers to agricultural practices that have been used for generations, relying on natural resources, manual labor, and traditional knowledge passed down over time. Challenges in Traditional Farming Methods Low Productivity Unpredictability Inefficient Resource UseLabor Intensity Lack of Market Access Pests and Diseases Soil Degradation @IABAC.ORG
- 3. Predictive analytics for yield forecasting. Cost reduction and efficiency improvement. Precision farming for optimal resource use IMPORTANCE OF DATA ANALYTICS IN FARMING @IABAC.ORG
- 4. Data Collection: IoT sensors, drones, satellite imagery. Data Processing: Cloud computing and storage. Data Analysis: AI, ML, and big data tools. KEY COMPONENTS OF DATA ANALYTICS IN FARMING @IABAC.ORG
- 5. APPLICATIONS OF DATA ANALYTICS IN AGRICULTURE Soil health analysis and monitoring. Crop monitoring and pest detection. Water resource management and irrigation. Climate and weather pattern predictions. @IABAC.ORG
- 6. Increased yield and productivity. Reduced costs through efficient input use. Early detection of pests and diseases. Better decision-making with accurate forecasts. BENEFITS TO FARMERS @IABAC.ORG
- 7. High initial costs for technology and equipment. Lack of digital literacy among farmers. Data privacy and security concerns. CASE STUDIES AND SUCCESS STORIES @IABAC.ORG
- 8. Integration with AI and robotics. Real-time analytics for on-the-spot decisions. Global trends and sustainable farming solutions. FUTURE OF FARMING WITH DATA ANALYTICS @IABAC.ORG