Description
Currently, the FreshScan AI application only displays the freshness of the latest scan, which limits its utility for long-term quality monitoring. This issue proposes a comprehensive Fish Freshness Trend Analytics Dashboard for vendors, regulatory authorities, and consumers to inspect freshness trends.
The dashboard will visualize daily and weekly freshness trends, vendor improvements, regional averages, and geographical heatmaps. We will implement interactive, responsive charts using custom-designed, styled SVG components styled specifically for the neon/brutalist dark mode theme. This avoids large external libraries and provides absolute visual control. Users will be able to filter data by species, date ranges, and vendor locations to identify trends, seasonal variations, and quality spikes.
Technical Implementation Details
- Analytics Endpoint: Build a new backend endpoint
/api/v1/scans/analytics in main.py aggregating daily and weekly averages.
- SVG Charting: Create a responsive
AnalyticsTrends.tsx component drawing clean SVG lines, grid overlays, and interactive hover dots.
- Regional Metrics: Implement widgets showing regional averages and vendor performance indicators.
- Tabs Integration: Incorporate this dashboard directly into
/analysis or as a secondary tab.
Description
Currently, the FreshScan AI application only displays the freshness of the latest scan, which limits its utility for long-term quality monitoring. This issue proposes a comprehensive Fish Freshness Trend Analytics Dashboard for vendors, regulatory authorities, and consumers to inspect freshness trends.
The dashboard will visualize daily and weekly freshness trends, vendor improvements, regional averages, and geographical heatmaps. We will implement interactive, responsive charts using custom-designed, styled SVG components styled specifically for the neon/brutalist dark mode theme. This avoids large external libraries and provides absolute visual control. Users will be able to filter data by species, date ranges, and vendor locations to identify trends, seasonal variations, and quality spikes.
Technical Implementation Details
/api/v1/scans/analyticsinmain.pyaggregating daily and weekly averages.AnalyticsTrends.tsxcomponent drawing clean SVG lines, grid overlays, and interactive hover dots./analysisor as a secondary tab.