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AI DASHCAM

MX04 AI Dashcam 4 Channel ADAS DMS for Commercial Fleet

MX04 AI Dashcam 4 Channel ADAS DMS for Commercial Fleet - AI Dashcam from Pictor Telematics.

Real-time monitoring
Fleet safety
Cloud dashboard
GPS tracking
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9,00,000+
Devices sending data via our platform since 2014
7,000+
Paying customers with live vehicles and assets since 2014
118+
Indian cities with active customers since 2014
12+
Years in industry
Overview

About MX04 AI Dashcam 4 Channel ADAS DMS for Commercial Fleet

MX04 AI Dashcam 4 Channel ADAS DMS for Commercial Fleet — AI Dashcam solution from Pictor Telematics.

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Downloads

MX04 Dual AI Dash camera V1.1-20230921 MX04 JT-T 1078-2016en MX04 JTT 808-2011 Protocol-English.pdf MX04 JTT 808-2019-English-20241121 (2) MX04 network protocol_V2.0.0-JT808-2019-20240407 (2) MX04-AI-protocol-with-logo
Resources

Downloads & documentation

MX04 Dual AI Dash camera V1.1-20230921 PDF download
MX04 JT-T 1078-2016en PDF download
MX04 JTT 808-2011 Protocol-English.pdf PDF download
MX04 JTT 808-2019-English-20241121 (2) PDF download
MX04 network protocol_V2.0.0-JT808-2019-20240407 (2) PDF download
MX04-AI-protocol-with-logo PDF download
FAQ

Frequently asked questions

Choose based on vehicle type, deployment scale, and monitoring objective. For most buyers, the best process is pilot first, validate data quality and workflow fit, then scale with the model that gives reliable operations and manageable total cost of ownership.
A complete implementation usually includes device setup, platform configuration, alert-rule tuning, and user onboarding. The exact scope depends on your rollout size, integration needs, and whether additional modules such as fuel sensing or video are included.
MX04 AI Dashcam 4 Channel ADAS DMS for Commercial Fleet can improve visibility, response time for operational exceptions, and reporting discipline. Financial and safety gains are typically strongest when teams define baseline KPIs and run consistent review and coaching workflows after go-live.
MX04 AI Dashcam 4 Channel ADAS DMS for Commercial Fleet is an AI-powered dashcam that records road footage while providing real-time driver behaviour monitoring and GPS tracking. It captures HD video (1080p/720p), stores footage locally, and syncs critical events to the cloud for fleet managers.
Yes. Our dashcams combine video evidence and tracking in a format that supports safety reviews, incident documentation, and regulated fleet workflows.
MX04 AI Dashcam 4 Channel ADAS DMS for Commercial Fleet records in 1080p Full HD or 720p HD depending on the model. Dual-channel versions capture both road-facing and driver-facing footage. Video is stored on an SD card with optional cloud backup for incident evidence.
MX04 AI Dashcam 4 Channel ADAS DMS for Commercial Fleet uses AI-based driver monitoring to detect distraction, drowsiness, phone use, and smoking. Alerts are sent in real-time to fleet managers, helping reduce accidents and improve driver safety.
Yes. MX04 AI Dashcam 4 Channel ADAS DMS for Commercial Fleet records and stores video locally on an SD card. When 4G connectivity is available, it uploads critical events (collisions, harsh braking, speeding) to the cloud. Offline recording continues seamlessly.
Dashcam pricing varies by features—single/dual channel, 4G connectivity, and AI capabilities. Contact Pictor for a competitive quote. We offer fleet discounts and flexible payment options for businesses.
Video storage depends on SD card capacity (typically 32GB–128GB) and recording settings. Loop recording overwrites old footage. Critical events are uploaded to cloud storage and retained as per your subscription plan.

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Pan-India installation
1 year warranty
24×7 support
Secure deployment
Product content standards

Written by

Pictor Telematics Product Documentation Team · Specifications and Deployment Guidance

Reviewed by

Mr. Rajesh Kumar · Founder Director & Chief Executive Officer

Published

Jan 15, 2024

Last reviewed

Apr 10, 2026

Validation approach

Product information is reviewed against technical specifications, installation constraints, and operational usage patterns from deployments since 2014.

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