Trail Camera Farm and Fleet

Trail Camera Farm and Fleet

Date Time: August 18, 2025
Reading volume: 12
Author: YUWEI

Trail Camera Farm and Fleet


As one of the world’s leading agricultural powers, Brazil’s farm economy is expanding at an astonishing pace. According to the Brazilian Ministry of Agriculture’s latest 2024 data, over 580,000 agricultural enterprisesare registered nationwide. Among them, more than 60% of medium- and large-scale farms operate dedicated fleets(including transport trucks, agricultural trailers, and irrigation vehicles), ranging in size from 10 to 200 vehicles.

 Trail Camera Farm and Fleet

However, as farm operations expand (with some sugarcane and soybean plantations spanning hundreds of kilometers) and transport demand surges (e.g., during coffee harvest season, daily transport volume rises by 40%), traditional fleet management methods—relying on manual logs and paper waybills—can no longer cope with critical challenges such as:

 

1. Difficulty tracking dispersed vehicles

2. Slow response to emergencies

3. Lack of accountability in safety incidents

 

Chinese company YUWEIhas introduced an AI-powered Fleet Tracking Camera System, integrating high-precision positioning, real-time video, and risk alerts. This solution is increasingly seen by Brazilian farm owners as an essential tool for reducing costs and boosting efficiency.

 

Why Do Farms Need an Intelligent Tracking Camera System?

To understand the value of fleet tracking, let’s examine the typical scenarios and challengesfaced by Brazilian farms:

 

Scenario 1: Vehicles “Lost” Across Regions

Brazil’s main agricultural regions (soybeans, corn) are concentrated in the Midwest (Mato Grosso, Goiás), while processing plants and export ports are mostly in the South (São Paulo) and Northeast (Recife).

 

For example, a truck traveling from Mato Grosso to Santos Port covers over 1,500 km, crossing rainforest, plateau, and highways. Traditionally, farms could only rely on driver phone calls or periodic GPS updates. Once the vehicle entered a signal dead zone (e.g., parts of the Amazon basin), the dispatch center lost all visibility—leading to delivery delays, route diversions, and cargo theft risks.

 

Scenario 2: Agricultural Machinery Efficiency & Safety

Large farms (e.g., sugarcane plantations over 5,000 hectares) often deploy 10+ machines simultaneously(harvesters, seeders, etc.). Timely coordination is crucial—for example, a trailer must arrive within 1 hour after a harvester finishes its task. Manual dispatching often causes bottlenecks such as machines waiting for trailersor trailers running empty.

 

On average, Brazilian farms lose over 3% of annual revenuedue to inefficient fleet coordination. Additionally, complex operating environments (night work, muddy fields) increase risks of fatigue driving and unsafe maneuvers, which are difficult to monitor manually.

 

Scenario 3: Cargo Loss and Disputes

Farm fleets transport perishable produce (fruits, coffee beans)or high-value machinery (e.g., imported seeders). Traditional management relies on pre-loading photos and post-delivery signatures. If cargo is damaged (e.g., rain exposure, theft), investigations can take days, often without sufficient evidence—leading to financial disputes and even legal battles.

A 2023 survey by the Brazilian Agribusiness Association (ABAG) revealed that 42% of farms suffered financial losses due to unclear responsibility during transport.

 

YUWEI Fleet Tracking Camera System

To address these needs, YUWEI launched the AI Fleet Tracking Camera System (Model: V8N).

Its core features—high-precision positioning, multi-lens video monitoring, and ADAS/DSM smart alerts—enable full-chain, visualized, and traceable fleet management.

    AI DASH CAM

1. Real-Time Tracking

① Dual-mode positioning module (GPS + Beidou + GLONASS), with INS backup navigationin low-signal zones such as the Amazon. Accuracy: ±2.5 meters.

② Each vehicle is equipped with:

 

a. 360° panoramic camera

b. Forward ADAS camera

c. Driver Status Monitoring (DSM) camera

Fleet managers can view vehicle locations, routes, and environments in real time via mobile app or PC.

③ Video playback allows review of any time point.

 

Case Study:

A soybean plantation in Mato Grosso adopted the YUWEI system, reducing vehicle “lost connection” rates from 18% to 0.5%, and improving on-time interstate deliveries from 72% to 95%.

 

2. Intelligent Management

Built-in ADAS (Advanced Driver Assistance System)and DSM (Driver Status Monitoring)provide:

 

① Safety Alerts: Immediate notifications for speeding, harsh braking, or lane departures. Events are logged with video evidence.

② Fatigue Monitoring: Detects prolonged eye closure, yawning, or phone usage; triggers in-cabin voice alerts and manager notifications.

③ Cargo Protection: Monitors unusual vibration/tilt (e.g., cargo shifting, door not properly closed), preventing avoidable losses.

 

Data Example:

A coffee cooperative in São Paulo reduced driver-caused accidents by 67%and cargo loss rates by 41%within six months of adopting YUWEI.

 

3. Dispute Resolution

① All driving trajectories, videos, and alerts are stored in the cloud (with local backup option).

② Managers can export PDF/Excel reports anytime.

③ In case of disputes (e.g., cargo damage), managers can retrieve video and sensor data to clarify responsibility.

 

Example: If coffee beans arrive wet, the system can show whether the truck door was improperly closed during rainfall.

 

Why Brazilian Farmers Choose YUWEI

Unlike generic fleet systems, YUWEI is tailored for Brazil’s agricultural context:

 

1. Language & Interface: Full Portuguese support (UI, alerts, reports), reducing training time.

2. Climate Adaptation: Cameras designed to withstand heavy rain and heat, operating between -20°C and 70°C—ideal for Brazil’s tropical savanna climate.

 

For Brazilian farms, fleets are more than just transport tools—they are the backbone linking planting, processing, and sales.

Through its “Vision + Data”approach, YUWEI not only answers fundamental questions—Where is the vehicle? Is it safe? What about the cargo?—but also provides long-term optimization insights (e.g., analyzing accident-prone routes, refining logistics planning).

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