FarmSense Launches AI-Powered Pest Monitoring System Called Smart Trap
Niko Pajkovic — December 14, 2021 — Business
References: farmsense.io & retail-insight-network
FarmSense, an American agricultural tech startup, has announced the launch of Smart Trap, an ML-Augmented smart pest monitoring system designed to help farmers improve insect monitoring and crop management.
The new system leverages machine learning algorithms and predictive analytics to automate the process of real-time insect identification. What this means is that farmers will be able to use the tech to accurately identify harmful insects in their crops in real-time, allowing them to make effective and timely decisions regarding pest control.
Smart Trap is a complete IoT-based system, meaning it utilizes in-field optical sensors, algorithmic technology, and cloud-based computing to streamline the insect monitoring and crop management process. SmartSense hopes that the new technology will lead to farmers using fewer pesticides and insecticides as it will remove much of the guesswork associated with managing pests.
Image Credit: FarmSense
The new system leverages machine learning algorithms and predictive analytics to automate the process of real-time insect identification. What this means is that farmers will be able to use the tech to accurately identify harmful insects in their crops in real-time, allowing them to make effective and timely decisions regarding pest control.
Smart Trap is a complete IoT-based system, meaning it utilizes in-field optical sensors, algorithmic technology, and cloud-based computing to streamline the insect monitoring and crop management process. SmartSense hopes that the new technology will lead to farmers using fewer pesticides and insecticides as it will remove much of the guesswork associated with managing pests.
Image Credit: FarmSense
Trend Themes
1. Smart Pest Monitoring - The AI-powered Smart Trap from FarmSense uses machine learning to improve insect monitoring and crop management, paving the way for continued innovation in automated pest management systems.
2. Real-time Insect Identification - The utilization of machine learning algorithms and predictive analytics for real-time insect identification in Smart Trap marks a significant move towards more efficient and effective pest control methods.
3. Iot-based Agriculture - Smart Trap's use of in-field optical sensors and cloud-based computing highlights the growing trend towards IoT-based systems in agriculture, and presents opportunities for further innovations in the field.
Industry Implications
1. Agriculture Technology - FarmSense's Smart Trap represents a disruptive innovation opportunity in the agriculture technology industry, allowing for more efficient and sustainable crop management through accurate pest monitoring.
2. Machine Learning - The application of machine learning algorithms to pest management in Smart Trap highlights the potential for further innovations in machine learning for improved crop management and sustainability.
3. Cloud Computing - Smart Trap's use of cloud-based computing demonstrates opportunities for further integration of cloud-based systems in the agriculture industry, potentially revolutionizing the way farmers manage crops and track data.
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