Big Data Platform for Smart Aquaculture
Step 7: Iterative feedback
During the pilot, formal feedback mechanisms must be in place so that users can systematically report on the usefulness and accuracy of platform outputs. Feedback should cover alert thresholds, forecast accuracy, interface usability, data entry burden, and the relevance of reports generated. Extension services and their agents play a key role in facilitating data quality and in capturing user perspectives, especially when staff turnover is high.
The Smart Data Platform can improve data quality by enforcing quality data entry through mechanisms such as geofencing, photographic evidence, and calendar-driven reporting. This enhanced data quality in turn improves the possibilities and quality of subsequent analysis. Keeping an up-to-date inventory of farm inputs is a repetitive task that can be greatly simplified with mobile-assisted data collection. Inventories are extremely useful for disaster recovery support, maintenance of feed-stock, and understanding farm losses due to feed quality deterioration and misaligned feeding patterns.
All feedback should be documented and used to refine models, interfaces, and alert thresholds before scaling. This iterative loop between user experience and technical development is what distinguishes a platform that is genuinely useful from one that is merely functional.
Use the checklist below to verify that all key elements of this step have been addressed or refer to the overall checklist to ensure all recommended actions are planned or completed: