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Business Registration. No 286-88-02459   CEO. Sunghoon Bae, Jihyun Yoon   Call. 02-6959-0966   Email. willog.info@willog.io

Business Registration. No 286-88-02459

CEO. Sunghoon Bae, Jihyun Yoon

Call. 02-6959-0966   Email. willog.info@willog.io

HQ. 06158 Willog, 9F, 507, Samseong-ro, Gangnam-gu, Seoul, Korea

USA. 19700 S. Vermont Ave, Suite 200, Torrance, CA 90502

Asia. 1 Finlayson Green Rd, #18-01, Singapore 049246

Japan. 15F, 1-17-1 Toranomon, Minato-ku, Tokyo 105-6415

Fleet Performance Diagnosis

Invisible transport inefficiencies — AI finds them.

Collect GPS, speed, and stop-duration data in real time to precisely analyze every trip. Compare actual driving against the optimal route, with AI auto-detecting unnecessary detours and excessive stops.

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Near Seattle Terminal

Arriving at Seattle Terminal in 15 mins.

ETA: 10/13/2025 10:00
On Schedule
Fleet Performance Diagnosis

Invisible transport inefficiencies — AI finds them.

Collect GPS, speed, and stop-duration data in real time to precisely analyze every trip.

Request a Free Demo
Device sensors detect...

Near Seattle Terminal

Arriving at Seattle Terminal in 15 mins.

ETA: 10/13/2025 10:00
On Schedule

Invisible damage during transport

causes billions of dollars in losses every year.

Route Deviations and Unnecessary Detours

A segment that should take 3 hours via the optimal route is arriving in 4 hours 30 minutes. Actual distance is 40% longer, but the cause is unknown.

Abnormal Stop Analysis

A short-distance trip takes 2.5× longer than expected. Where and how long the vehicle stopped is impossible to verify. Each driver has different stop patterns, making standardized management hard.

Per-Driver Efficiency Variance

Same route, same vehicle — driver A averages 3 hours, driver B averages 4 hours 30 minutes. No data shows who is efficient and who needs improvement.

Abnormal Trips Discovered Too Late

Only after a customer claim do you learn 'delivery was late.' Without real-time monitoring, response during the incident is impossible.

Invisible damage during transport

causes billions of dollars in losses every year.

Route Deviations and Unnecessary Detours

A segment that should take 3 hours via the optimal route is arriving in 4 hours 30 minutes. Actual distance is 40% longer, but the cause is unknown.

Abnormal Stop Analysis

A short-distance trip takes 2.5× longer than expected. Where and how long the vehicle stopped is impossible to verify. Each driver has different stop patterns, making standardized management hard.

Per-Driver Efficiency Variance

Same route, same vehicle — driver A averages 3 hours, driver B averages 4 hours 30 minutes. No data shows who is efficient and who needs improvement.

Abnormal Trips Discovered Too Late

Only after a customer claim do you learn 'delivery was late.' Without real-time monitoring, response during the incident is impossible.

The mechanism

AI-Driven Diagnosis of Transportation Inefficiencies and Driver Abusing Using Vehicle Operation Data.

AI-Driven Diagnosis of Transportation Inefficiencies and Driver Abusing Using Vehicle Operation Data.

Step 01

Real-Time Vehicle Operation Data Collection

Capturing location, speed, and stoppage time for every vehicle at one-minute intervals, ensuring complete and accurate records of all fleet operations.

Step 02

Optimal Route Analysis

Calculating the shortest distance and fastest time using OSRM (Open Source Routing Machine), then comparing against actual routes driven to identify inefficient segments.

Step 03

AI Anomaly Classification

Analyzing vehicle operation data with AI to automatically classify abnormal patterns

Step 04

Actionable Insights Delivery

Detecting abnormal driving in real time while improving overall transport efficiency through driver-specific improvement points and long-term pattern analysis.

Step 01

Real-Time Vehicle Operation Data Collection

Capturing location, speed, and stoppage time for every vehicle at one-minute intervals, ensuring complete and accurate records of all fleet operations.

Step 02

Optimal Route Analysis

Calculating the shortest distance and fastest time using OSRM (Open Source Routing Machine), then comparing against actual routes driven to identify inefficient segments.

Step 03

AI Anomaly Classification

Analyzing vehicle operation data with AI to automatically classify abnormal patterns

Step 04

Actionable Insights Delivery

Detecting abnormal driving in real time while improving overall transport efficiency through driver-specific improvement points and long-term pattern analysis.

Improving vehicle turnover rates and reducing unnecessary short-distance stops

Without Willog Intelligence

Transit time: 2 hours 15 minutes actual vs. 50 minutes expected for a 30km short-distance route
Transit time ratio: 2.7 (270% of expected)
Root cause: Unknown
Action taken: None possible

With Willog Intelligence Fleet Performance Diagnosis

AI-generated stoppage timeline: automatically created
Total stoppage time: 90 minutes (67% of total transit time)
Anomaly classification: Excessive short-distance stoppage pattern
Action taken: Driver warning issued and retraining initiated

Improving vehicle turnover rates and reducing unnecessary short-distance stops

Without Willog Intelligence

Transit time: 2 hours 15 minutes actual vs. 50 minutes expected for a 30km short-distance route
Transit time ratio: 2.7 (270% of expected)
Root cause: Unknown
Action taken: None possible

With Willog Intelligence Fleet Performance Diagnosis

AI-generated stoppage timeline: automatically created
Total stoppage time: 90 minutes (67% of total transit time)
Anomaly classification: Excessive short-distance stoppage pattern
Action taken: Driver warning issued and retraining initiated

Fleet Performance Improvement Cases

Short-Distance Abusing Detection
Urban Delivery

Short-Distance Abusing Detection

Analyzing GPS-based vehicle operation data with AI to diagnose abnormal stoppage patterns and track driver-specific improvement outcomes.

Long-Distance Route Optimization
Regional Transport

Long-Distance Route Optimization

Comparing optimal and actual routes with AI to identify recurring detour patterns and improve average driving distance.

Cold Chain Temperature Management
Frozen Goods

Cold Chain Temperature Management

Analyzing temperature data with AI to diagnose the root causes of standard deviations, managing quality compliance through cooling and equipment improvements.

Short-Distance Abusing Detection
Urban Delivery

Short-Distance Abusing Detection

Analyzing GPS-based vehicle operation data with AI to diagnose abnormal stoppage patterns and track driver-specific improvement outcomes.

Long-Distance Route Optimization
Regional Transport

Long-Distance Route Optimization

Comparing optimal and actual routes with AI to identify recurring detour patterns and improve average driving distance.

Cold Chain Temperature Management
Frozen Goods

Cold Chain Temperature Management

Analyzing temperature data with AI to diagnose the root causes of standard deviations, managing quality compliance through cooling and equipment improvements.

Short-Distance Abusing Detection
Urban Delivery

Short-Distance Abusing Detection

Analyzing GPS-based vehicle operation data with AI to diagnose abnormal stoppage patterns and track driver-specific improvement outcomes.

Long-Distance Route Optimization
Regional Transport

Long-Distance Route Optimization

Comparing optimal and actual routes with AI to identify recurring detour patterns and improve average driving distance.

Cold Chain Temperature Management
Frozen Goods

Cold Chain Temperature Management

Analyzing temperature data with AI to diagnose the root causes of standard deviations, managing quality compliance through cooling and equipment improvements.

How Efficiently Is Your Fleet Really Operating?

How Efficiently Is Your Fleet Really Operating?

Willog Intelligence uncovers hidden inefficiencies in your fleet operations and delivers actionable optimization strategies.

Willog Intelligence uncovers hidden inefficiencies in your fleet operations and delivers actionable optimization strategies.

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