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Manufacturing
Future-Ready Manufacturing: Partnering in your journey to a sustainable manufacturing enterprise
Highlights
- Automakers are somewhat reticent to share in-vehicle data with other ecosystem players due to concerns over data privacy and security. The other associated sectors which include insurers, car lessors, and radio cabs, however, seeks in-vehicle data for getting a level playing field to drive growth.
- Some of the areas where data is critical are customer experience management, repair and maintenance, and insurance.
- A connected, collaborative, and cognitive ecosystem will ensure safe exchange of such data while addressing the critical issue of cybersecurity.
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Data holds the key
Modern vehicles are equipped with software to generate a trove of in-vehicle data.
This includes data on engine performance, vehicle speed, location, distance travelled, and driver behavior to assess rash driving. That data can be tracked, consumed, and monetized by original equipment manufacturers (OEMs) and organizations from allied sectors such as repairs and maintenance, insurers, leasing companies, radio cabs, and parking zone providers.
OEMs, however, resist sharing that data with the associated sectors as they envisage two scenarios. One is a potential revenue loss as some of them may be in the same business. The other is a potential cybersecurity breach such as compromise on data privacy and protection.
Other ecosystem players, on the other hand, demand fair market competition as this in-vehicle data potentially paves the way for significant economic growth for them.
Such a situation calls for fair-trade practices between the two sides, with information security as paramount, to leverage the data for a win-win for all players across the automotive ecosystem.
Power of in-vehicle data
Connected vehicles generate a trove of data that can be used by various ecosystem players.
Key areas where this data can drive significant impact include:
Customer experience: Data obtained through autonomous driver assistance systems (ADAS), mobile phones as a secured device replacing vehicle keys, alerts through remote diagnostics of vehicle health and self-healing systems, and remote programing of routes can go a long way in improving driver experience and making the journey safer.
Repairs and maintenance:
- By placing RFID tags on vehicles during servicing, dealers can retrieve data on customer profile, usage history, and car model (chassis number, vehicle features, and others), to process information on how the car is being used by the customer and proactively suggest personalized services. For example, a set of data points on a vehicle’s health will help them make recommendations on oil change, wheel balancing, and tyre pressure.
- By embedding mobile broadband chips and on-board computers, a vehicle can transfer telematics data to generate performance trends, fuel efficiency, safety, breakdown location, and impact assessment. The data will also issue real-time alerts on tyre pressure, vehicle speed, mileage, fuel consumption, oil level, engine status, battery charge status, steering angle, and outside temperature of the vehicle.
Insurance:
Data from telematics (black box) can also capture breach of speed limits at regular intervals and rash driving which can help insurers analyse driving behaviour and fix premiums and settle claims. Data shared between vehicles and infrastructure components, such as traffic lights and parking meters, will allow connected cars to be safe and aware of the presence of pedestrians and cyclists. Similarly, data shared between vehicles (V2V) will help connected cars to be aware of the other’s speed, location, and direction. As the automotive industry aims to enter the age of driverless and connected cars, data exchange will be the bedrock for the transition.
Mobility as a service (MaaS):
Connected vehicles offer a plethora of services for drivers and dealers based on real-time information during the journey such as concierge services and real-time traffic information. Geo fencing allows dealers to set a virtual fence around showrooms using GPS. Once set, it can push notifications flashing special offers that would get delivered to customers’ phones when they enter the fenced area.
A safe, secure, and symbiotic growth of the entire ecosystem merits consideration of four key aspects – business purpose, data ownership, cybersecurity, and cost of data acquisition.
In this regard, some questions that OEMs should ask their ecosystem partners are:
- What kind of data are they planning to collect? Is there a clear business use case for each?
- What are the success factors and who are the beneficiaries? Are they end users, service providers, OEMs, government, or society?
- When do they need such data, and do they need it in real time or on request?
A collaborative future
A connected, collaborative, and cognitive ecosystem, marked with safe and secure data sharing, will chart the next growth wave for the auto sector.
Data can be retrieved from the connected vehicles (sub ecosystems) into a central cloud repository, or a cloud-based data lake. This data, then subjected to an artificial intelligence (AI) and machine learning (ML) system, can be used by business to business (B2B) and business to consumer (B2C) players across the automotive system to drive customer experience. The data transaction will happen through universally accepted and safe and secure APIs. The B2B and B2C customers will also have provisions to receive and get information through multiple means.
Connected vehicles offers access to various players in the public ecosystem like service stations, signalling infrastructure, gas stations, parking zones, geo satellites for navigations, and police towers. It is thus important to have a robust cybersecurity system in place to prevent accepting unauthorized access and unsafe request for misuse.
Figure 1: A connected, collaborative, and cognitive ecosystem for the automobile sector
Putting the guardrails
While data sharing improves user experience and opens new revenue streams, it calls for extreme caution.
And that is because of the potential threats to information privacy, vehicle safety, and most of all, the safety of human life. A robust cybersecurity model, coupled with policies, would promote significant transparency between the OEMs and the allied sectors resulting in a healthy synergy. The model must consider the following three aspects:
- Cybersecurity through a vehicle’s lifecycle of sales to scrap: OEMs would need to collaborate with their application system development partners and co-create in-built vehicle applications during the vehicle design stage to ensure security and safety. That would also take into consideration all the potential threats from the handover of vehicle to the customer till the end of its product life.
- Control on software upgrade management system: When a smart vehicle is being used, it gets connected to various external systems to get more services. OEMs and allied companies, that provide such services, access smart vehicles in different times through IoT with necessary user permissions to keep updating their software applications through patches. This necessitates a safe and secure transfer of data.
- Safe channel for time-bound sharing of data: If an organization does not use every minute to its advantage, it allows room to hackers to cause irreversible damage. It may take multiple business days, or even weeks, to detect security anomalies, hacking attempts, or any suspicious network activity. A time-bound data sharing model is therefore an imperative from a cybersecurity perspective.
The road ahead
Sharing of in-vehicle data is imperative but tackling the inherent challenges is the first step in this journey.
A connected, collaborative, and cognitive ecosystem between OEMs and associated players, who offer servitization to elevate customer experience, will transform the automotive landscape. However, that must be accompanied by robust cybersecurity practices and policies at a time when data breaches across industries have become far too frequent.
Often, companies with a bigger market share collect and process a bulk of the in-vehicle data and refuse to share it with others, citing privacy concerns. That adversely impacts other players such as car dealers and garage keepers who are also looking to grow by leveraging the data. The automotive industry must ensure fair competition for its upliftment.
- The bottom-most layer predominantly enables the compute, network, and storage as a foundation, coupled with public and hybrid clouds, and the existing enterprise IT and manufacturing systems of record such as enterprise resource planning (ERP) systems, manufacturing execution system (MES), and product lifecycle management (PLM).
- The layer above enables foundational large language models (LLMs) for a variety of knowledge management use cases—auto or aero LLMs, sourcing and procurement data lake, and warranty analytics and insights embedded in a frictionless DevSecOps ecosystem.
- The next layer constitutes AI-enabled purposive and contextual task agents that enable various moving parts of AI, such as fine-tuning of AI models on an ongoing basis, establishing the necessary guardrails for responsible and ethical implementation of AI, and a strong ML and LLM capability for continuous learning by the models.
- The final layer comprises task agents that interact with each other in a seamless fashion with a human-in-the-loop for validation, verification, and disambiguation.
