Since the COVID-19 pandemic, auto sales have dropped by 13.05 percent in India and 15 percent in the US in FY20-21. As social distancing and avoiding crowds have become the new normal, there is a rise in used cars sales in the US. This is a challenging time for the auto industry and one may or may not be able to regularly get their vehicles checked. However, IoT and IIoT have embraced the challenge and have useful tools to maintain cars through predictive processes. The use of IoT or IIoT is cost-effective and provides autonomy to the consumers in maintaining their cars. Predictive car maintenance has the potential of optimizing the uptime and reducing the downtime and the labour cost associated with car repairs.

Predictive car maintenance models

The predictive car maintenance models are based on the support vector machine (SVM) algorithm. The SVM algorithm’s aim is to find the best decision boundary or hyperplane based on extreme data points or vectors, also known as support vectors, provided to a machine. The machine is trained to aid the classification of the desired data. The hierarchical modified fuzzy support vector machine (HMFSVM) is a layered predictive algorithm and is a variant of MFSVM and FSVM models, with SVM as its basis. All these algorithms run simultaneously and the machine learns to recognize various patterns in the data.

The base variables for this algorithm are vehicle registration date, registration numbers, odometer reading, etc. The derived variables for this model are the age of the vehicle, the count of each service type, the average labour cost, and the average cost of the spare parts. These variables are the inputs to the model to arrive at robust predictions. This helps the OEMs (original equipment manufacturers) to troubleshoot the errors in the code and increase the longevity of the vehicle. It also helps the consumer with advanced alerts for the predictive damage that the car may have in the future. This in turn will save the consumers from falling into the trap of unnecessary repairs offered by the technicians.

The technologies used by these models are IoT, Big Data, Data Analysis, AI, ML (machine learning), cloud computing, wireless connectivity such as 5G, and BI (business intelligence) to provide an up-to-date analysis of the cars and track the mechanical failures in real-time. These technologies help provide an insight into the car data and reduce the warranty costs by 15-20 percent. Cloud computing helps to manage Big Data and the on-demand scalability of the vehicle. Thus, keeping the customers and OEMs in the loop for the maintenance of cars. The alerts will be sent to the users on their smartphones enabling real-time analysis of the cars.

Making the smart cars smarter

Ukraine-based N-iX, formerly Novellix, is a startup that uses the HMFSVM model to provide predictive car maintenance and has a significant presence in Europe and the US. The company’s automotive software development provides services to tier 1 and tier 2 suppliers, enabling them to prevent failures and deal with a large amount of data. Their software provides efficient cloud computing solutions, Big Data platforms, and Vehicle-to-Everything (V2X) solutions. The company’s AI and ML algorithms help reduce maintenance costs and the longevity of the vehicle.

The CarFit Puls company, whose headquarters is based in CA, USA, uses NVH (noise, vibration, and harshness) automotive technology powered by AI to create a library of vehicle vibration data. Their predictive model provides the dealers and service providers a platform to keep a check on the vehicle’s health. The company’s car vibration tracking device, an electronic wearable for vehicles, lower the maintenance cost and provides transparency to consumers about how their vehicle works.

T-Matix provides OEMs IoT devices and platforms to aid their consumers’ car maintenance capabilities without the need to code. The use of sensor technology via connectivity, APIs, dashboards, apps, and data protection helps companies take a lead in a highly competitive market of automobiles. Pegasystems or Pega provides services to the automotive industry to fix the vehicle before it fails. Their predictive maintenance solutions provide sensor data, event streaming, in-memory database, real-time analysis, and end-to-end automation to deliver the “process of everything”.

With offices based in the UK, India, Canada, China, and the US, Quantzig focuses on converting large and complex data into intelligent and actionable insights. Their auto predictive tech solutions backed by AI and ML prevent unforeseeable damage to the auto parts and dynamic management of vehicles. By tapping into the potential of IoT and Big Data analysis, Quantzig wants to help industries grow by mitigating risk, sales, customer, and market analysis.

Functioning on similar principles, Quectel, based in China, is a home-bound global supplier of cellular IoT modules and antennas to provide AI solutions to the automotive industry with human insights. Their cellular and GNSS modules are designed to help OEMs create smart vehicles with durable and efficient hardware. Thus, helping the consumers stay up-to-date with the condition of their vehicle and in-advance alerts of the future damage.

What’s next?

The automotive industry is predicted to use 300 million new IoT connections by 2025. By the end of this decade, the industry is forecast to be worth $81 billion with 9 percent CAGR growth across Europe, China, and the US. The automotive car industry alone is predicted to reach $60 billion with 40 percent growth of the mileage-based sector in Europe and 35 percent of new car sales in the US. As smart cities continue to flourish and 5G connectivity is becomes mainstream, predictive maintenance will become an asset for the automotive car industry.

Not only are electronics becoming smarter day by day, but consumers are also becoming more informed in the choices they make. Gone are the days where customers would be forced to make expensive repairs without being provided ample information about the damage to their cars. IoT is making sure that such follies are removed from our discourse forever. The gap that is exploited by the middle-men between the OEMs and customers will soon be reduced to nothing. It is time to empower the consumers and keep them safe from the expense that could have never been predicted.