Energy storage stations generate massive volumes of data daily through their video surveillance systems. Under traditional architectures, all video streams are transmitted back to a central platform for analysis, creating significant bandwidth strain and high response latency, while large amounts of irrelevant data drown out genuine abnormal events. Performing AI analysis at the data source has become a critical challenge for intelligent operation and maintenance in the energy storage sector.
To address this need, Joyware Electronics Co., Ltd. has launched the AI Super Brain for energy storage stations. Deployed at the station-level equipment room, this product operates within the edge processing layer of the intelligent auxiliary control system, performing real-time AI analysis on front-end video streams. It enables "data stays within the station, alarms upload instantly," substantially reducing bandwidth usage and accelerating response times. The system provides early warning support for the station's intelligent auxiliary control infrastructure, automatically detecting risks such as personnel violations, fire and smoke, perimeter intrusions, and various meter anomalies, while issuing tiered alerts and initiating coordinated responses.
Smart Detection and Alerting: Comprehensive Coverage of Safety and Operations
In safety supervision, the AI Super Brain supports zone intrusion detection, fire and smoke detection, personnel compliance checks, and construction vehicle monitoring. For personnel compliance, the system automatically verifies whether workers are properly wearing safety helmets, work attire, and following operational procedures. Any violations trigger immediate alerts, activate audio warning systems, and push notifications to the management platform, creating records for subsequent review and performance assessment. In equipment maintenance, the AI Super Brain can identify LED digits, counter readings, switch status indicators, signal lamp states, air breaker conditions, and oil temperature or oil level gauge readings, replacing manual periodic inspections with timely abnormal condition detection.
Edge Computing: On-Site Data Processing with Instant Alerts
The AI Super Brain performs AI inference locally through edge computing, uploading only "alert images, short video clips, and structured event data." This approach ensures sub-second alert responses while minimizing upstream bandwidth costs. The system combines real-time analysis with stored playback capabilities, creating a closed-loop video data architecture at the station level that satisfies both pre-incident warning and post-incident traceability requirements.
The Xingjian Large Model: Advancing from Recognition to Comprehension
The AI Super Brain is built on the Xingjian Large Model, independently developed by Joyware Electronics Co., Ltd. Previously, this model achieved large-scale deployment in the transportation sector. As the first product applying the Xingjian Large Model to energy storage scenarios, the AI Super Brain leverages the model's multimodal fusion capabilities and decoupled visual architecture. This overcomes the limitations of traditional small models in visual cognition, offering enhanced scene generalization that enables precise identification of broader and subtler abnormal events within complex, multi-objective energy storage environments. Combined with multimodal retrieval and intelligent agent interaction, it achieves a critical transition from "smart recognition" to "deep understanding."
The AI Super Brain supports customization of multiple algorithms, allowing flexible configuration of detection scenarios to suit the differentiated requirements of various stations. Currently, the product is operational at energy storage station sites. Together with the intelligent auxiliary control platform, it forms the smart core layer of Joyware Electronics Co., Ltd.'s energy storage solutions, delivering complete station-level intelligent support for safe and efficient facility operations.