iotin agriculture use and many more1.pptx

iot in agriculture

1. Contents Introduction to IOT in agriculture Benefits of IOT in agriculture Sensors used in IOT agriculture Data analysis and decision making in IOT agriculture Examples of IOT in agriculture Challenges in implementing IOT in agriculture Future of IOT in agriculture Disadvantages Conclusion

2. Introduction to IOT in agriculture The integration of Internet of Things (IOT) in agriculture is revolutionizing the industry by enabling real-time monitoring and management of farming processes.

3. Benefits of IOT in agriculture 1 Efficient Resource Utilization IOT allows for precise water usage and optimal resource allocation, leading to reduced waste and increased productivity. 2 Enhanced Crop Monitoring Real-time data from sensors helps in monitoring crop health, detecting diseases, and identifying growth patterns. 3 Automated Processes IOT enables automation of agriculture operations, saving time and labor costs while improving accuracy.

4. Sensors used in IOT agriculture Soil Sensors Measure moisture, temperature, and nutrient levels to optimize irrigation and fertilization . Weather Sensors Collect data on temperature, humidity, wind speed, and rainfall to aid in weather-informed decision making.

5. Mechanical sensors.  These sensors are used to measure soil compression or mechanical opposition. The mechanical sensor is pushed through the soil. As it passes through the soil, it documents the holding forces that result from the cutting, smashing, and displacing of soil. Soil mechanical resistance is recorded in a unit of pressure and points out the ratio of the force necessary to go into the soil.  Electrochemical sensors.  These sensors help in gathering chemical data of the soils by detecting specific ions in the soil. They provide information about the pH and soil nutrient levels. Typically, these sensors are mounted on special sleds. Soil samples are sent to a lab for analysis and the most accurate data collection. The goal of these sensors is to gather highly specific information about the soil to make informed decisions. 

6. Data analysis and decision making in IOT agriculture Predictive Analysis Utilize historical and real-time data to foresee trends, crop conditions, and market demands. 2. Prescriptive Insights Recommend precise actions based on analyzed data, optimizing farming operations for better results. .

7. Examples of IOT in agriculture Smart Farms Fully automated and monitored farms with IOT-driven climate and resource control. Precision Agriculture Utilizing IOT to precisely manage farming and enhance overall yield and quality. Crop Monitoring Real-time monitoring and analysis of crops through IOT sensors and systems.

8. Challenges in implementing IOT in agriculture Data Security Ensuring the security of sensitive data collected from farm sensors and devices. Infrastructural Limitations Challenges in providing stable internet connectivity in rural farming areas.

9. Future of IOT in agriculture Scaling IOT Integration Widespread adoption of IOT technology across diverse areas of agriculture. Advanced AI Integration AI-driven analytics for predictive and automated agricultural management.

10. DISADVANTAGES Cost : Implementing IoT technology can be expensive, especially for small-scale farmers or those in developing countries . Security Risks : IoT devices are vulnerable to cyber-attacks, which could compromise sensitive data or disrupt operations . Data Privacy Concerns : Collecting and storing large amounts of data from IoT devices raises privacy concerns, especially regarding the ownership and use of that data.  

11. Conclusion The bottom line is that Agriculture with IoT is changing the future of farming for the better . With more accurate data and a more connected system, farmers are able to make better, more informed decisions about their crops , which in turn leads to a better yield and less waste . Not to mention, with the world's population only getting bigger, it's more important than ever to have a system in place that can sustain our growing food needs.

12. Reference   [1] Tragos, E. Z., Angelakis, V., Fragkiadakis, A., Gundlegard, D., Nechifor, C. S., Oikonomou, G & Gavras, A. (2014, March). Enabling reliable and secure IoT-based smart city applications. In 2014 IEEE International Conference on Pervasive Computing and Communication Workshops (PERCOM WORKSHOPS) (pp. 111-116). IEEE. [2] Shah, J., & Mishra, B. (2016, January). IoT enabled environmental monitoring system for smart cities. In 2016 International Conference on Internet of Things and Applications (IOTA) (pp. 383-388). IEEE. [3] Pasha, S. (2016). Thing Speak based sensing and monitoring system for IoT with Matlab Analysis. International Journal of New Technology and Research, 2(6)