Fleet AI — Operator Dashboard (Mock)

Uptime

Fleet Uptime (est.)

98.7%

Goal ≥ 98.0% • operator-facing metric

Avoided

Estimated Downtime Cost Avoided

$18,420

Semi / diesel economics (mock)

Queue

Priority Actions (next 14 days)

9

Risk-ranked to reduce surprises

ROI

Projected ROI (pilot estimate)

3.9×

Savings vs. effort + cost

Priority Queue

“Tell me what to fix first”

Fleet Manager Notifications

Auto-generated from patterns

Maintenance-first actions are ranked by downtime risk

Context GPS + Cameras support faster resolution

Fleet Health Table

Searchable snapshot • mock values

Unit	Status	Next Recommended Action	Due Window	Risk

Live Telemetry

Simulated stream • abnormal behavior triggers alerts

Live Event Log

Last 10 events for selected unit

Time	Signal	Observation	Action

Predictive trend + threshold + correlation + persistence

Semi focus DPF/EGT/rail pressure/charging stability

Alerts

All alerts across fleets • mock feed

GPS Tracking

Live simulated positions • supports maintenance + dispatch context

Live

Selected: —

Mode: Demo

Unit Telemetry (GPS Layer)

Status—

Speed—

Heading—

Lat/Lon—

ETA to Yard (mock)—

Maintenance Risk—

Click a marker to select unit

Location Feed

Last 8 updates

Maintenance Context

Why GPS matters for preventable maintenance

“Service window planning”

Use route + yard proximity to schedule repairs when the truck is naturally near your shop or a preferred vendor.

Cuts downtime

Better than roadside events

“Derate / risk recovery”

If an aftertreatment or charging anomaly escalates, GPS gives immediate context for routing to the safest/closest service point.

Protects loads

Reduces tow exposure

Real Product would use real GPS (ELD/telematics), geofences, and route history

Demo is simulated with smooth motion

Cameras

Road-facing + Driver-facing • supports safety + maintenance verification

Road-Facing Camera Demo feed • switch channel on the right

Live Feed (Mock)

In the real product, this panel would render a truck camera stream (RTSP/WebRTC), store clips for events, and link camera events to alerts (e.g., smoke/overheat event context, roadside breakdown verification).

Demo Mode Stream Ready

CH 1 • Road

Camera + Maintenance

Keep it aligned with Fleet AI’s core

Verification of “symptoms”

Use camera clips to validate smoke, overheating indicators, leaks, or driver-reported symptoms that correlate with sensor patterns.

Reduces false positives

Faster roadside decision-making

When an alert fires (EGT, coolant temp, voltage dips), camera context helps decide: continue, derate strategy, or route to service now.

Cuts emergency costs

Channels

Select a feed

Event Clips (Mock)

Linked to alerts

Real Product WebRTC/RTSP ingest + cloud clips + permissions

Demo channel switching + optional device camera

AI Advisor

Fleet-scoped assistant • maintenance + cost + growth

Guardrail Mike answers only using this demo fleet’s data + assumptions

Business ROI, downtime exposure, scheduling strategy

Pilot Reports

Simple, sellable summaries operators actually use

30-Day Pilot Summary (Mock)

Uptime trend, prevented urgent events, recommended maintenance windows, and a clear next-step plan.

Cost Avoidance Breakdown (Mock)

Conservative view of avoided tow/emergency labor + time-loss reduction by early scheduling.

Maintenance Priority Plan (Mock)

A simple list: “Do now / Do soon / Can wait” with reasons and due windows.

Operator-friendly reporting: avoid jargon, show decisions. A fleet manager should be able to act in under 60 seconds.