Industry Case Studies
Real-world deployments, data-driven results
GreenCharge — Nationwide EV Charger Operations Platform
The client operates 2,000+ EV chargers nationwide across 5 different brands, with incompatible device protocols and manual inspection-based fault response. Average fault resolution time exceeded 8 hours, and operational costs remained high.
Deployed the JIZHI TECH IoT platform, unifying all charger devices via OCPP protocol. Built real-time monitoring dashboard with intelligent alerting and automated dispatch. Integrated with existing ERP for closed-loop asset management and maintenance work orders.
Three months after launch: automatic fault detection rate increased from 15% to 92%, average fault resolution time reduced to 2.5 hours (69% improvement), operations labor costs reduced by 40%, device online rate improved from 91% to 98.5%.
Haiyun Scenic Area — Smart Tourism IoT Data Platform
The scenic area spans over 30 km² with peak daily visitors exceeding 100,000 during holidays. Traditional dispatch methods could not perceive real-time crowd distribution, and safety hazard detection lagged behind.
Deployed the Smart Tourism Data Platform with iBeacon plus GPS dual-mode positioning for real-time visitor location awareness. Built WebSocket real-time messaging channels for safety alerts and navigation info, integrated crowd heatmaps and geo-fence alerts.
During the 2025 National Day Golden Week, the system handled a peak of 120,000 concurrent online users with message push latency under 200ms. Safety incidents decreased by 60% year-over-year, satisfaction scores improved from 3.8 to 4.6 out of 5.
Precision Manufacturing — AI Quality Inspection Local Deployment
A precision component manufacturer relied on manual visual inspection for quality control, facing low efficiency, inconsistent standards, and high miss rates. Cloud AI services could not be used as product blueprints were classified.
Adopted JIZHI TECH Enterprise AI Local Deployment solution. Deployed a workstation-grade GPU server on the factory floor and used LoRA to fine-tune a general-purpose vision model for defect detection. Training completed with only 2,000 labeled images.
Inspection efficiency increased 5x (from 800 pieces/person/day to equivalent 4,000), miss rate dropped from 3.2% to 0.5%, false positive rate at 1.8%. All data and models remained 100% on-premises and passed security audit.