Project Background

A large‑scale mining enterprise in Laos undertakes intensive transportation of earth‑rock and mine slag. A large number of dump trucks travel between mining working faces and barite spoil yard. Under complex mountain site conditions, trip statistics previously relied on manual counting, which brought high labor cost. Manual registration is prone to omission and error especially during night shifts. Material volume was estimated by experience without objective reference. Disputes frequently occurred between mining company and fleets over trips and volume without photo evidence. Mountain mining area suffers unstable network, conventional network‑dependent devices often lose data.
The client required an automatic mining‑truck counting & volume‑measuring robot system, to realize AI auto‑identification for dump trucks at spoil yard, automatically count trips, record volume data, capture photos for evidence, support offline local storage and cloud report generation, to achieve unattended measurement for overseas mine site.

Project Pain Points

1. High labor cost for on‑site attendance: 24‑hour two‑shift operation requires on‑site staff, human errors easily happen on night shifts.
2. Deviations in trip statistics: frequent vehicle arrivals cause manual omission and over‑counting, leading to reconciliation conflicts.
3. Empirical volume estimation: no automated volume‑detection solution, settlement lacks objective basis.
4. Insufficient evidence: no vehicle snapshots for reviewing disputes on trips and cargo volume.
5. Poor network in overseas mountain mine: network signal fluctuates, ordinary devices risk data loss.
6. Difficult multi‑fleet management: multiple transport fleets operate simultaneously. Manual ledger sorting brings heavy workload for vehicle ID, fleet, work zone and material classification.

Solution

Chongqing Jinyun Machinery deployed the automatic mining‑truck counting & volume‑measuring robot system for this Laos mining project. The whole system consists of AI high‑definition snapshot host, machine‑vision acquisition unit, edge‑computing terminal and cloud management platform, installed at key passage of barite spoil yard.

Powered by AI visual algorithm, the system automatically recognizes dump trucks passing through spoil yard and counts transport trips. Basic information including vehicle ID, fleet, work zone, material type, cargo volume and unit price can be pre‑configured. When trucks pass detection zone, complete counting records are generated automatically with real‑scene snapshots stamped with timestamp, vehicle ID, fleet, work zone, material, volume and unit price.

Edge offline cache is supported. All records are stored locally upon network outage and auto‑synchronized to cloud after network recovery to prevent data loss. Managers can check full counting details remotely via PC backend and mini‑program. Data can be filtered by fleet, vehicle ID, time and material. Auto‑generated reports can be exported for reconciliation and settlement between mine operator and transport fleets, realizing unattended auto‑measurement at spoil yard.

Hardware Advantages

‑ Industrial‑grade AI snapshot host, stable for outdoor mine environment with high temperature, heavy dust and large day‑night temperature difference in Laos.

‑ Machine‑vision unit with infrared night supplement and strong‑light suppression, clear snapshot both day and night.

‑ Local edge computing terminal, AI inference processed on‑site instead of fully relying on cloud network, well‑adapted to weak‑signal mine sites.

‑ Outdoor protective enclosure with dust‑proof and water‑proof performance for long‑term open‑air deployment.

‑ Complete offline cache mechanism, data preserved during network failure and auto‑re‑uploaded, fit unstable network conditions of overseas mines.

Core Software Functions

1. AI automatic vehicle counting: auto‑recognize dump‑truck passage and count trips without manual operation.
2. Fleet & vehicle archive management: pre‑store vehicle ID, fleet, work zone, material, volume and unit price, bound to each record automatically.
3. Snapshot evidence storage: capture real‑scene photos for every passing vehicle with watermarked timestamp and location for dispute traceback.
4. Offline edge cache: local data storage under poor network, auto‑sync after network recovery for stable overseas mine operation.
5. Multi‑dimension data filter: filter counting records by fleet, vehicle ID, shift, material and time.
6. Auto report export: one‑click export statistical reports for reconciliation and settlement between mine and transport fleets.

On‑site Application Effect

The automatic mining‑truck counting & volume‑measuring robot system is officially put into operation at Laos barite spoil yard and achieves unattended operation.

When trucks pass detection area, trips are counted automatically with complete records and snapshots. On‑site manual counting duty is eliminated. Reliable identification works even for night‑shift operation, greatly reducing omission and mis‑registration caused by manual work.

Faced with network fluctuation in mining area, records are cached locally and synchronized automatically once network resumes to guarantee data integrity. Domestic managers can remotely access Laos mine transportation data, including trip quantity, cargo volume, material information and on‑site snapshots.

Auto‑generated reports simplify manual ledger work, effectively mitigate settlement conflicts over trips and volume, and improve digital management capability of overseas mining site.

Customer Benefits

1. Reduce on‑site manpower: realize unattended spoil‑yard measurement, cut 24‑hour manual counting post and lower mine labor cost.
2. Objective counting reduces reconciliation disputes: AI counting plus photo evidence provides solid reference for settlement between mine and fleets.
3. Adapt to weak‑network overseas mine: edge offline cache avoids data loss under unstable mountain network.
4. Full‑day‑night adaptability: stable identification and snapshot under strong daylight and dark night, matching mine 24‑hour continuous production.
5. Remote digital supervision: domestic managers obtain overseas mine transport statistics remotely, one‑click report export streamlines settlement workflow.