Project Background

Beijing Construction Engineering Group undertakes a large‑scale earth‑rock work project. Multiple excavators and dozens of dump trucks work simultaneously. Loading trips and equipment working hours were traditionally recorded manually.
Manual registration frequently causes missing and wrong loading records. Working hours filled in by drivers bear risks of false reporting. Traditional gate‑based counting devices cannot cover scattered working faces and fail to reflect real loading volume of each excavator. Paper‑document sorting brings heavy workload for project settlement and team accounting, and there is no photo evidence for trip disputes. An excavator‑mounted counting & timing system is required to realize auto loading recognition, working‑hour statistics, photo evidence and cloud‑based data aggregation directly on working faces.

Project Pain Points

1. Working faces are far from site gates: gate‑access counting cannot reflect real loading trips of excavators.
2. Large manual‑recording errors: loading trips and working‑hours reported by drivers often contain omissions and false data.
3. Lack of on‑site evidence: no photos or videos for reviewing trip‑hour disputes.
4. Complex management for multi‑excavator operation: manual ledger sorting costs massive manpower with mixed excavators and dump trucks.
5. No real‑time data synchronization: managers cannot remotely monitor operation progress of each excavator.

Solution

Chongqing Jinyun Machinery delivered and deployed batches of Excavator Counting & Timing Devices for Beijing Construction Engineering Group project. The complete set includes cab touch terminal, high‑definition snapshot camera and main control module, installed inside excavator cabs.
Based on AI visual recognition, the system automatically identifies loading events when excavators finish loading dump trucks, counts loading trips and captures on‑site photos with timestamp and excavator ID. It also collects working‑hour data and distinguishes effective working duration from idle standby time. Local touch terminals allow drivers to check counting and hour data on site. All loading records, working‑hour logs and snapshots are uploaded to cloud platform in real‑time. Managers can view loading details and hour statistics of every excavator remotely via PC and mini‑program. Data filtering and auto report export support team measurement and project settlement. Statistics and evidence are completed directly on excavation working faces without relying on site barrier gates.

Hardware Advantages

‑ Excavator‑special touch terminal with shock‑resistance for heavy‑vibration cab environment.

‑ Industrial‑grade HD snapshot camera, stable photo capture under strong sunlight, dust and cloudy field conditions.

‑ Integrated main control unit with simple wiring, convenient batch installation and commissioning for large‑scale project deployment.

‑ Wide‑voltage power adaptation fits various excavator brands, dust‑proof and vibration‑resistant for long‑time heavy‑duty construction‑site operation.

‑ Local offline data cache. Records are stored locally under poor network and auto‑re‑upload after network recovery to avoid data loss.

Core Software Functions

AI auto loading counting: visual recognition of loading actions to count trips automatically without manual input.

1. Excavator timing & working‑hour statistics: automatically calculate effective working hours and idle standby duration.
2. On‑site photo evidence storage: capture photos for each loading event with timestamp and excavator ID for dispute review.
3. Local cab terminal display: drivers check real‑time loading quantity and working‑hour data inside cab.
4. Cloud management platform: remotely access full excavator data on PC and mini‑program; support data filtering and one‑click report export for team measurement and financial settlement.

On‑site Application Effect

Jinyun excavator counting & timing devices are installed on multiple excavators of the project. Loading recognition and statistics are completed directly on working faces instead of merely relying on gate‑barrier data.
The system counts trips and captures photos automatically when loading finishes, eliminating false reports and manual‑recording errors. Working hours are split between effective operation and idle status to reflect real equipment performance. Under poor‑network conditions, data are cached locally and synchronized automatically after network recovery to guarantee record integrity.
Project managers remotely obtain loading volume and hour details of each excavator with attached loading photos for traceable verification. Paper‑ledger workload is greatly reduced. Team measurement and accounting are simplified. Earth‑rock transportation trips are effectively controlled and the whole project achieves higher digital‑management level.

Customer Benefits

1. Reflect real‑working‑face performance: statistics are generated on excavator side, making up for the limitation of gate‑only counting.
2. Prevent manual falsification risks: AI auto counting‑timing reduces manual filling and avoids false reports on trips and working hours.
3. Full‑process photo evidence: real‑scene photos for each loading provide solid proof and reduce settlement conflicts.
4. Offline‑capable for poor‑network sites: local cache protects data in weak‑signal mine and construction‑site environment.
5. Digital efficient accounting: cloud auto‑aggregated reports simplify team measurement and project settlement and cut on‑site management manpower input.