Agriculture

Apply Computer Vision Technology To Enhance Precision Agriculture & Livestock Operations From Farm-Through-Production

Camera-based data collection for AI solutions is enabling massive change in the way organizations across the agriculture industry to manage their businesses with efficiency and accuracy that was previously impossible.

USE CASE

LIVESTOCK COUNT & HEALTH MONITORING

Challenge

Many manual processes and tasks involved in livestock management can cause inefficiencies, delays and unavoidable inaccuracies leading to a significant impact on cost. Accurate livestock counts are crucial to profitable operations, but manual tasks are difficult and prone to human error. Visual inspection of livestock is arduous, monotonous and is susceptible to condition-based challenges. Manual inspection and measurements of livestock can cause late detection of disease and increase risk of impact on other animals.

Solution

Video cameras enhance human operations with accurate data collection, analysis and benchmarking. Accurate count of livestock as they exit transports and move through processes, holding areas and pens impacts all aspects of operations with immediate positive impact on the bottom line. Rich data can be collected via cameras and computer vision models can be trained to automatically detect and classify a wide array of issues, such as animal gait, measurement, behavior, etc. Predictions and real-time alerting of any event or visual input can be instantly sent to the appropriate individuals. The Sense easy to use dashboard and flexible interoperability with other systems enables intelligence to be shared and used by all team members.

USE CASE

CROP DISEASE DETECTION

Challenge

As populations continue to grow, urbanization is causing a reduction in farmland. The pressure on the agriculture industry to find effective and safe ways to improve quality and quantity production is increasing. The monitoring of crop growth mainly relies on subjective human judgment and is not timely or accurate. Traditional agricultural management methods must be complemented by innovative device and data technologies, such as camera-based AI, to improve knowledge and productivity accurately for high-quality operations and high-yield production.

Solution

To improve monitoring and timely action based upon real-world visual data input, Sixgill computer vision technology detects subtle changes in crops due to malnutrition, disease, weeds or pests. Drones offer a highly effective source for visual data. The data can provide the basis for immediate remediation, data for planning and other types of visualizations such as crop mapping to track problem areas and improvements. Sixgill AI solutions provide prevention and control capabilities and a broad spectrum of crop monitoring advantages including increased cost effectiveness, minimized errors, and high efficiency with continuous data collection and analysis.

USE CASE

CROP DISEASE DETECTION

Challenge

As populations continue to grow, urbanization is causing a reduction in farmland. The pressure on the agriculture industry to find effective and safe ways to improve quality and quantity production is increasing. The monitoring of crop growth mainly relies on subjective human judgment and is not timely or accurate. Traditional agricultural management methods must be complemented by innovative device and data technologies, such as camera-based AI, to improve knowledge and productivity accurately for high-quality operations and high-yield production.

Solution

To improve monitoring and timely action based upon real-world visual data input, Sixgill computer vision technology detects subtle changes in crops due to malnutrition, disease, weeds or pests. Drones offer a highly effective source for visual data. The data can provide the basis for immediate remediation, data for planning and other types of visualizations such as crop mapping to track problem areas and improvements. Sixgill AI solutions provide prevention and control capabilities and a broad spectrum of crop monitoring advantages including increased cost effectiveness, minimized errors, and high efficiency with continuous data collection and analysis.

USE CASE

PRODUCT GRADING & QA/QC PACKAGING

Challenge

Manual grading and QA/QC practices for agricultural products lack standardized techniques and require tedious human inspection tasks. Today, the production aspects of food are as important as the product itself. The consumer is questioning the safety and quality of the food they consume, as well as where, how and by whom it’s produced and packaged. This increased attentiveness to food producers by the ultimate consumer is top of mind and is driving the implementation of new technology-based processes.

Solution

The efficiency and simplicity of Sixgill’s platform and AI IoT solutions are gamechangers. Camera-based systems provide the consistent detailed monitoring and ML models provide the immediate detections needed in the product grading and packaging process. Among the possibilities are automated validation of correct quality designations, sorting, labeling, weight measurements and SKU tracking. The Sense system can also detect issues or defects such as foreign objects or punctured packaging assisting with health and safety standards compliance. A centralized system for ML model management and device control provides production operations teams one source for issues and intelligence.

Whether you need our Enterprise AI services to build custom models or have the team to build or upload models and manage them within Sense, please let us know how we can help solve your use case requirements and the needs of your business.

Contact us today to request a demo of Sense.