HomeLatest NewsOpinionHow can embedded Telematics and Generative AI transform your fleet business?

How can embedded Telematics and Generative AI transform your fleet business?

Telematics has grown in use recently. Understanding the integration of generative AI and embedded telematics cloud platforms is crucial for businesses to leverage richer data, optimize ROI, and enhance organisational benefits effectively.

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Over the last few years, more businesses and fleet organisations have begun to rely on the use of telematics that can benefit operational efficiencies and the bottom line. Many companies in just about all industries have a fleet of vehicles that are used for business purposes.

These vehicles are often viewed as a cost centre for the business, but the use of telematics is helping these businesses gain better control over various costs involved with operating the fleet.

What is telematics?

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A wealth of asset data is now available because of fleet telematics. Telematics collects information about asset usage, driver behaviour, fuel consumption, and diagnostic trouble codes (DTCs) directly from an asset using GPS tracking and on-board diagnostic reading capabilities.

Fleets can use telematics data to improve overall utilisation for higher ROI, find the root of expensive issues and behaviours, and strengthen maintenance procedures. The old way of using this telematics data is a plug-in device like a dongle, OBDII, Blackbox etc., which is clumsy, expensive and ineffective.

 Pay attention – not all providers are the same

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The market is flooded with TSPs selling their hardware and proclaiming to deliver upon these expectations, but the reality is that fleet operators are simply not experiencing the ROI, and are facing an epidemic of inaccurate data, unreliable analytics and poorly designed user interfaces. The data cannot be consistently or efficiently ingested, aggregated or normalised to make sense of a fleet’s risk performance.

While there are many telematics solutions available today, it’s important to pay close attention to the holistic solution. The data from different vehicle manufacturers is many times different, so it’s important to ensure you’re working with a data provider that has a platform capable of standardising all data so all parties involved (fleet managers, maintenance, insurers, etc.) can make apples-to-apples comparisons and analysis of all vehicle data. Not all telematics and data providers have this capability.

Embedded telematics platform for TSPs for fleets

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The purpose of the embedded telematics platform is to provide a single point of access to all TSPs, fleet managers and drivers. It offers a new level of visibility into the operation of the vehicle, so it can be used to improve efficiency and reduce costs.

Technology advancements have freed telematics solution providers from the constraints of their proprietary hardware and allowed them to serve clients using any third-party device, creating a device-agnostic solution. An open telematics platform uses the numerous data sets produced by a vehicle to make data transparent, enable simple access, and offer creative solutions.

Fleets today are working with partners can standardise embedded telematics data from multiple OEMs and organise into a single format using FMS standards. Integrating third-party data is only possible through an open model system where data is shared in a variety of ways, laying the foundation for achieving the best results for fleet operations.

The only way for fleets to gain insight from their is a cloud-based platform which can integrate with any TSPs, understand the dynamic behaviours of the entire fleet.

Fleets can cut expenses by using embedded telematics, which also increases asset ROI. Two of the biggest costs for a fleet are maintenance and fuel; information gathered from telematics, including asset location, helps fleets better control these costs by reducing idling, optimising routes, and identifying mechanical problems early for quick resolution.

But early issue detection does more than just enhance asset maintenance. Furthermore, it increases field and vehicular safety. Additionally, fleets can enhance driver coaching and training to further develop a culture of fleet safety and lower driver behaviour-related service costs because telematics records unsafe driving behaviours like speeding and abrupt braking.

The role of embedded telematics in reducing maintenance costs

Embedded fleet telematics tools are a great resource for managing and analysing any fleet because they provide a wealth of vehicle data, including details on the condition of the vehicles. Receiving vehicle information directly from OEMs is a great way to enhance the fleet maintenance strategy and track KPIs.

Fleet managers can receive real-time connected vehicle data in a cloud-based platform to automate maintenance workflows and promptly address vehicle issues as they arise by combining embedded telematics data with integrated fleet management software.

In order to prevent vehicle downtime and boost fleet efficiency, managers need to have the most visibility possible into the status of their vehicles, their maintenance schedules, and the results of inspections.

Fleet technology closes information gaps and gives managers up-to-the-minute information on all assets. A cloud-based platform can give real-time information about the condition of each vehicle so they can stay informed of any problems and decide what fleet maintenance is required to prevent downtime.

Preventive maintenance (PM) schedules are typically based on mileage, but manually tracking odometer readings is labour-intensive and frequently prone to error. Paper-based systems do not give fleet managers accurate, real-time updates to guarantee that PM tasks are completed on schedule.

By utilising cloud-based platform that can integrate with your TSPs, odometer readings can be automatically uploaded into fleet management software, ensuring managers have a structured way to manage fleet maintenance and never fall behind on PM tasks.

Generative AI plays a pivotal role in fleet management by analysing vast amounts of information from embedded telematics giving fleet managers valuable insights to improve fleet efficiency, reduce costs, and optimise performance.

Improving driver safety with embedded telematics

Data from a cloud-based platform and artificial intelligence can also be used to improve driver safety. Generative AI can monitor real-time driver actions, such as hard braking, excessive speeding, intense acceleration, aggressive lane changes, harsh turning, seat belt usage, and harsh cornering driver actions, such as hard braking, excessive speeding, intense acceleration, aggressive lane changes, harsh turning, seat belt usage, and harsh cornering.

The most interesting part is that AI continuously learns from real-time data, enhancing its decision-making capabilities even further and adapting to diverse driving conditions. Generative AI plays a pivotal role in fleet management by analysing vast amounts of information from embedded telematics giving fleet managers valuable insights to identify risk, save time, and create value to keep drivers safe and to drive competitive value in the marketplace.

Generative AI can monitor real-time driver actions, such as hard braking, excessive speeding, intense acceleration, aggressive lane changes, harsh turning, seat belt usage, and harsh cornering driver actions, such as hard braking, excessive speeding, intense acceleration, aggressive lane changes, harsh turning, seat belt usage, and harsh cornering.

Reducing fuel cost with embedded telematics

With the rise of connected vehicles, fleet managers are faced with a wealth of data, but simply collecting this data is not enough. Fleet managers need to accurately analyse it to determine the total cost of ownership (TCO) for their vehicles. Accurate data is crucial in calculating TCO and optimising it, but analysing and interpreting data can be challenging.

Therefore, fleet managers are increasingly turning to solution providers to help them accurately calculate TCO and identify areas for optimisation. And a central, cloud-based platform is the most effective solution to manage operations and securely transfer data between systems.

Monitoring fuel costs and consumption is crucial for obtaining an accurate total cost of ownership (TCO) for most fleets since fuel typically forms the largest expense, close to 60% of all operating costs for a fleet.

AI-powered algorithms analyse and monitor fuel consumption patterns and identify inefficient driving behaviours, such as excessive idling, harsh acceleration, or harsh braking.

Generative AI gives real-time actionable insights on driver behaviour that can help optimise fuel efficiency and reduce operating costs. Fleet Managers can optimise fuel usage, thereby reducing costs, minimising environmental impact, and optimising Total Cost of Ownership (TCO)

While telematics has been increasingly used over the last few years, it’s important to understand how the new generative AI and embedded telematics cloud platform can benefit a business so that the resulting richer data can be maximised for the right ROI and organisational benefits.

The author is co-founder and chief operating officer, Cerebrum X. Views are personal.

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Sumit Chauhan
Sumit Chauhan
Sumit Chauhan is the co-founder and COO of Cerebrum X. With a career spanning over 24 years, he has worked in various sectors including automotive, IoT, telecoms, and healthcare. His leadership roles have involved managing P&L responsibilities of nearly US $0.5 billion in companies such as Aricent, Nokia, and Harman.
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