Mobility

Fleet Intelligence

Data to outcomes

A modern commercial fleet — whether long-haul trucks, urban delivery vans, taxis, buses, EV charging-network vehicles or yellow goods at a port — generates terabytes of telemetry, location, driver-behaviour, energy and cargo data every day. Most of it sits dark. alticdigital’s Fleet Intelligence practice converts that data into measurable operational, safety, financial and ESG outcomes — combining telematics, computer vision, predictive analytics, AI agents and the ISSPL group’s heritage in marine, vehicle and industrial classification to deliver fleet operating models that insurers, regulators and CFOs all trust.

Fleet Intelligence — Data to Outcomes

Fleet intelligence use cases

01

Connected Fleet Telematics and Real-Time Operations

Vehicle-level telemetry ingestion (CAN bus, OBD-II, FMS, J1939, GPS); real-time fleet map with status, geo-fencing and exception alerts; dispatch and route optimisation; fuel and energy management; tyre and trailer monitoring; cold-chain telemetry; driver-vehicle assignment and hand-over workflows. Foundational layer on which every other fleet use case depends.

Connected Fleet Telematics and Real-Time Operations
Use Case 01

Vehicle-level telemetry ingestion (CAN bus, OBD-II, FMS, J1939, GPS); real-time fleet map with status, geo-fencing and exception alerts; dispatch and route optimisation; fuel and energy management; tyre and trailer monitoring; cold-chain telemetry; driver-vehicle assignment and hand-over workflows. Foundational layer on which every other fleet use case depends.

02

Predictive Maintenance and Total Cost of Ownership Optimisation

Machine-learning models that predict component failure (engine, battery, brakes, EV powertrain, transmission, HVAC) days to weeks ahead of incident; integration into workshop and parts-planning systems; condition-based servicing replacing fixed-interval servicing; warranty-claim automation; full TCO dashboards. Downtime drops 25–40%, mean-time-between-failure rises sharply.

Predictive Maintenance and Total Cost of Ownership Optimisation
Use Case 02

Machine-learning models that predict component failure (engine, battery, brakes, EV powertrain, transmission, HVAC) days to weeks ahead of incident; integration into workshop and parts-planning systems; condition-based servicing replacing fixed-interval servicing; warranty-claim automation; full TCO dashboards. Downtime drops 25–40%, mean-time-between-failure rises sharply.

03

Driver Behaviour, Coaching and Safety AI

In-cab video and audio AI; harsh-braking, harsh-cornering, speeding, distracted-driving and drowsiness detection; in-the-moment voice coaching; gamified leaderboards; driver-score sharing with insurers for usage-based premiums; incident reconstruction with auto-generated evidence packs; chain-of-custody video retention for legal and regulatory use.

Driver Behaviour, Coaching and Safety AI
Use Case 03

In-cab video and audio AI; harsh-braking, harsh-cornering, speeding, distracted-driving and drowsiness detection; in-the-moment voice coaching; gamified leaderboards; driver-score sharing with insurers for usage-based premiums; incident reconstruction with auto-generated evidence packs; chain-of-custody video retention for legal and regulatory use.

04

EV Fleet and Energy Management

State-of-Health, State-of-Charge and Remaining-Useful-Life analytics on EV battery packs; charge-scheduling against electricity tariffs and grid-services participation; range-aware dispatch and routing; vehicle-to-grid (V2G) revenue capture; second-life and recycling decision support; alignment with the EU Battery Regulation 2023/1542 and Digital Product Passport requirements.

EV Fleet and Energy Management
Use Case 04

State-of-Health, State-of-Charge and Remaining-Useful-Life analytics on EV battery packs; charge-scheduling against electricity tariffs and grid-services participation; range-aware dispatch and routing; vehicle-to-grid (V2G) revenue capture; second-life and recycling decision support; alignment with the EU Battery Regulation 2023/1542 and Digital Product Passport requirements.

05

Cargo, Compliance and ESG Reporting

Automated electronic Proof of Delivery; tachograph / Hours-of-Service compliance; ELD / smart tachograph data reconciliation; SCOPE 1, 2 and 3 emissions accounting per shipment; CSRD and ISO 14064 reporting feeds; automated driver-incident and regulatory filings; integration with customs and logistics partner systems.

Cargo, Compliance and ESG Reporting
Use Case 05

Automated electronic Proof of Delivery; tachograph / Hours-of-Service compliance; ELD / smart tachograph data reconciliation; SCOPE 1, 2 and 3 emissions accounting per shipment; CSRD and ISO 14064 reporting feeds; automated driver-incident and regulatory filings; integration with customs and logistics partner systems.

Benefits, value and beneficiaries

25–40% reduction in unplanned downtime; 10–20% reduction in fuel or energy consumption; 30–60% drop in serious driver-behaviour incidents; insurance premium reductions through usage-based models; faster, cleaner audits across HOS, emissions and proof-of-delivery; full audit trail across every mile.

Direct opex reduction on fuel, maintenance and insurance; revenue uplift through better asset utilisation and on-time delivery; lower legal and regulatory exposure on driver-hours and emissions; ESG and CSRD reporting readiness without spreadsheet gymnastics; safer drivers, safer roads, demonstrably safer fleets.

Chief Operating Officer; Head of Fleet and Transport Operations; Director of Logistics and Supply Chain; Head of Safety, EHS and Compliance; CFO and Insurance / Risk Manager; Head of Sustainability; Fleet Maintenance Manager; CIO. Front-line beneficiaries include the dispatcher, the workshop foreman, the driver coached in-cab, the safety officer and the insurance underwriter pricing real risk on real data.

Customer Challenges and the Need to Act

The dark data inside a fleet is the largest unmined asset on the balance sheet

Most fleet operators run on a 1995 operating model — fuel cards, paper proof-of-delivery, retrospective monthly utilisation reports and incident-driven maintenance. The data needed to run a 2026 operating model already flows out of the vehicle. The question is whether the operator has the platform, the AI and the assurance discipline to convert that flow into measurable margin. alticdigital was built to be that partner — anchored in the ISSPL group’s classification heritage and the engineering rigour that goes with it.

Relevant geographies

India United States Canada United Kingdom Germany France Netherlands Spain GCC Region Saudi Arabia United Arab Emirates Australia South Africa Brazil Mexico ASEAN Logistics Corridors

Let’s build your fleet intelligence platform

From connected telematics to predictive maintenance and ESG reporting, our team is ready to engineer your fleet operating model.

Backed by Industrial Heritage

50+ Years of Industrial Assurance

alticdigital is the technology subsidiary of ISSPL — a classification and certification group with five decades of industrial-inspection heritage. Every solution we deliver inherits this culture of rigour, traceability and audit-grade quality.

IEC 62443 — OT Security ISO 27001 — Information Security NIST CSF — Cyber Framework IACS Classification Standards