Smart Vehicles & IoT: Challenges and Opportunities in The Future of Mobility

Smart Vehicles & IoT: Challenges and Opportunities in The Future of Mobility

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By Dinis Guarda

In a world where everything is connected, what will be the role of smart vehicles and what changes it will bring to our lives? Self-driving cars are smart, and it takes correspondingly smart people and technology to build them. With so many benefits to be reaped from such innovation, the ICT industry is investing in its own future by supplying technology required by the largest automakers worldwide and rising consumer trends, wishing to bring about the digital transformation of driving.

Smart Vehicles & The Internet of Things

But the auto and ICT industries’ collaborative acceleration of smart car development does not come without its fair share of challenges. Digitised smart car technology is still in its primal stages; a feat of mechanical and electronic engineering that remains rudimentary. The stakes for smart car development are thus not only high because the outcome could be so overwhelming, but also because it is so uncertain. The road to digital transformation in the already high-tech realm of auto engineering is one which has yet to be drawn and driven, according to FAW (China’s first automotive firm to conduct R&D on smart cars).

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What are smart vehicles?

What makes a smart car? The Society of Automotive Engineers (SAE) in the United States offers tiered definitions, identifying different levels of automobile intelligence. The majority of car manufacturers aim to meet the requirements of SAE’s Level 3: cars able to control speed and steering programmatically and rely on the human driver to take over in dynamic situations, such as when bad weather interferes with the car’s sensors. In addition to real-time monitoring and braking capabilities, cars will require Artificial Intelligence, Big Data, cloud computing and other ICT technologies if they are to reach this level.

Of course, autonomy is not the only target; the integration of smart hardware and software has to meet safety standards as well. Deaths caused by traffic incidents in the US average about 20,000 a year – a steady figure which shows no sign of decreasing (omitting 2020 figures, when the pandemic drastically reduced road traffic altogether). Appropriately, smart cars are being developed with collision-avoidance capabilities, which may solve – or least alleviate – the problem of road traffic mortality, according to the US Department of Transportation. The American government is thus encouraging high-tech firms such as Google to apply their technology to smart car development, hoping to position the US as a leader in the smart car industry – the EU and Japan being the chief rivals.

The digitisation of smart cars can be split into three main areas: smart manufacturing, Artificial Intelligence (AI) and the Internet of Things (IoT).

Smart manufacturing

Leading automakers worldwide describe traditional car manufacturing as ‘serial’: ‘starting with product planning and engineering design, then [on] to experimentation and trial production, and from full-scale production to marketing and post-sales services.’ The advent of cloud capabilities from innovative ICT infrastructures disrupts this production line, using virtual platforms to push it into many parallel processes such as digital design and service platforms. This considerably improves production costs and efficiency and reduces the number of physical tests needed for a car to meet modern crash-safety standards thanks to cloud-based virtual collision technologies – the most important of which are currently 5G and V2X. In fact, Japan is positioning itself as a world leader in automated driving/Vehicle-to-Everything (V2X) standards.

AI

Smart cars rely on AI in relation to three specific domains: sensor fusion, route planning, and the use of AI and Big Data for multiple levels of data classification and delivery of results. Smart cars are projected to use on-board AI capabilities in the immediate future, with further support provided by cloud-based AI services. But as cloud and ICT technologies improve and innovate, cloud-based AI support is expected to become the primary director of smart cars, allowing them to perform functions such as determining the speed and direction at which other cars and people are moving, or indeed whether the objects it senses are people 0r cars (or even a barrier).

IoT

By endowing cars with more sensors, processors and software, passenger vehicles will become integrated carriers of digital transformation. In other words, smart car ambition is directly informed by IoT, which will not only permit cars to handle a wider range of scenarios, but will usher the automobile companies into a new – and unprecedentedly vast – realm of work. Indeed, companies which have traditionally belonged to the manufacturing industry are converting to be more service-oriented.

In order to fully investigate IoT’s capabilities in relation to the development of smart cars, we need to understand what exactly is IoT.

What is IoT?

“The internet of things (IoT) is a catch-all term for the growing number of electronics that aren’t traditional computing devices, but are connected to the internet to send data, receive instructions or both,” explains Josh Fruhlinger. These devices encompass a large spectrum, from gadgets like Alexa to internet-enabled sensors in farms and factories. By bringing the power of the internet, data processing and analytics to the real world of material objects, IoT blurs the boundaries between the digital and the physical. When a modern washing machine can be operated from a smartphone using an internet app, the person using it is directly engaging with the global information network; the very act of doing laundry is now part of an interconnected digital system.

In addition, the data-gathering capabilities of IoT is hugely beneficial to industry settings, where the data compiled by millions – if not billions – of embedded internet-enabled sensors serve as a reading key for companies wishing to assess ‘the safety of their operations’, ‘track assets’, ’reduce manual processes’, or even learn more about ‘people’s preferences and behaviour’ (Fruhlinger). Through IoT, the internet can now accelerate the processes of physical manufacturing and distribution in the same way it has been accelerating the research and dissemination of knowledge of decades.

The data-gathering capabilities of IoT is hugely beneficial to industry settings, where the data compiled by millions – if not billions – of embedded internet-enabled sensors

Opportunities with smart vehicles and IoT

IoT is therefore crucial to the development of smart vehicles, collating the data needed to refine the technology required to meet safety and efficiency standards. Indeed, traditional car wiring is insufficient as it is built on mechanics, from the engine and transmission system to the integrated electrical components such as electronic engine control. Smart cars require a new core platform, entirely independent of the traditional engine, transmission, braking, and steering systems – one that includes sensors and software intelligence that connect with GPS mapping, sensor fusion, AI, and a growing range of supercomputing platforms. This IoT-based architecture, named ‘interconnection architecture’ by FAW, is to connect cars to the cloud and vice-versa.

This creates rich opportunities for smart vehicles, accelerating the development of functions such as health and attention monitoring. Indeed, most road traffic incidents occur because the driver has become distracted or tired; with smart technology, cars may be able to determine when a driver’s capacities are compromised and take over driving control accordingly.

Challenges with smart vehicles and IoT

The first challenge with smart vehicles and IoT is an ethical one: sharing so much personal data could be met with intrusion of privacy accusations. Fortunately, as the world becomes increasingly digitised, cybersecurity standards are correspondingly reinforced; smart car manufacturers would do well to work closely with digital security consultants.

The second challenge concerns engineering: how does one build the technology mentioned in section IV? A health and attention monitor, for instance, cannot exist without Big Data analytics interpreting information about roadways, the environment, and expanding interactions. Another crucial core technology is dynamic mapping: traditional navigation systems are based on fixed maps, so how does one transcend these limits and construct new technologies to generate real-time maps that are dynamic and responsive to current conditions?

Smart car manufacturing firms will not only need to hire competent mechanical engineers, but a highly skilled R&D team able to master new practices and operating regimes that include, among others, environmental assessment and AI-based decision-making control. New technologies of this kind have already started to emerge; FAW has already introduced the concept of AllwayEye, the core function of which is to allow each car to capture data related to its immediate environment and upload it to the cloud. With all similarly equipped cars in the vicinity uploading and downloading situational information with the cloud, any accident, collision or hazard would be taken into account by the car’s in-built navigation programs, informed by cloud communication. This would allow drivers to reprogram their route in real-time.

Transforming traditional R&D models and choosing the best core technologies in order to respond to an increasingly complex technological revolution is the main challenge currently faced by the auto industry – and it is one that no car firm can answer alone. An example of successful teamwork in the field is FAW’s collaboration with Huawei: a Chinese giant that benefits from a rich ecosystem of partners in many industries.

Case studies and solutions by Huawei

As a leader in the ICT sector and pioneer in emerging technologies such as 5G, cloud computing and, especially, IoT, Huawei is strengthening its position in the smart vehicle market by developing and implementing new solutions. Eric Xu, Chairman of Huawei, said recently at the Huawei Global Analyst Summit 2021:

We will ramp up investment in components for intelligent vehicles, especially autonomous driving software. Vehicles are becoming more connected, intelligent, electric, and shared these days, and at the core of these trends is whether or not autonomous driving software can make truly autonomous cars a reality, and take us a step closer to entirely unmanned driving. With intense investment in autonomous driving software, our hope is to drive these trends forward as they facilitate the integration of the automotive and ICT industries, which in turn creates long-term strategic opportunities for Huawei. […] Once unmanned driving becomes a reality, we will see disruption in practically all adjacent sectors and trigger the most disruptive industry transformation the world will see in the next 10 years.

Huawei wants to become the chief provider of new components for intelligent vehicles, fuelling its investments in autonomous driving software such as enhanced communication capabilities, cloud services and optical networks. Indeed, autonomous vehicles rely on computing and cloud services to identify red or green lights, or possible obstructions and hazards. Huawei’s ICT expertise means it is strategically positioned to deliver these technological innovations. Moreover, Huawei has an entire unit dedicated to the development of full-stack ICT systems for the B2B market: the Intelligent Automotive Solution Business Unit. This creation of a highly specialised team means Huawei has a solid grasp of user requirements and considerable experience in design for the B2C market. The company’s ‘platform + ecosystem’ strategy anchors its user interface within the wider tech and automotive networks.

Being the tech giant that it is, Huawei has, unsurprisingly, partnered with some of the biggest names in the auto industry; namely Audi on L4 autonomous driving, and BAIC Group on its Arcfox models, providing the latter with solutions and components. But how exactly has Huawei earned its reputation for delivering innovative solutions?

Huawei has branded its Intelligent Automotive Solutions ‘Huawei HI’, powered by HarmonyOS and launched in October last year. HI aims to drive the upgrade of technologies in the automotive industry and develop leading intelligent electric vehicles, by adopting a new joint development model in which the company works with automakers and leverages its technological advantages to jointly design and develop high-quality cars. These will use the automaker’s brand and display HI’s logo on the car body, identifying the vehicle as one that uses the full-stack HI Intelligent Automotive Solution.

“HI delivers full-stack intelligent automotive solutions. We have accumulated 30 years of technical experience and are integrating with the automotive industry, as well as pursuing cutting-edge technological development to outperform competitors,” commented Wang Jun, President of Huawei’s Intelligent Automotive Solution Business Unit (IAS BU). “We firmly believe that the new model will help us develop ideal, intelligent EVs. As a result, we will achieve brand extension and strengthen China’s automotive industry, which currently focuses on size.”

HI’s acceleration of the development and production of smart vehicles relies on an all-new architecture for computing and communications, built on five pillars: intelligent driving, e-cockpit, intelligent electrification, connectivity, and an intelligent automobile cloud. This architecture – a Level 4 automated driving standard – is bolstered by powerful computing and operating systems for intelligent driving, e-cockpit and intelligent vehicle control; the operating systems in question are AOS, HOS, and VOS respectively. Powered by these computing and operating systems, vehicles can thus be defined by software, which Huawei believes will advance the development of new functions and ensure that customer experience is constantly improved.

Zooming in on the electrical appliances built into the smart vehicles by Huawei, it becomes apparent that the HI system is not only industry-leading in terms of sensors, central supercomputing, and algorithms, but also in terms of its self-improving capabilities: the use of AI allows the system to constantly learn and evolve on its own to become a smarter and better driver for consumers. One of the most advanced technologies developed by Huawei for smart vehicles is an intelligent electric system offering oil-cooling heat dissipation, providing better cooling effects and higher power outputs when at high speeds and thereby placing the car firmly within the 3-second club. Another notable innovation is the HI cockpit solution, which utilises Augmented reality head-up displays (AR-HUD) to turn a normal windshield into a 70-inch HD screen, allowing users to watch movies, play games, or attend video conferences while enjoying 7.1 surround sound. This same solution offers powerful visual recognition, semantic understanding, and advanced AI technologies; it can communicate in natural language and understand user gestures and expressions. A final innovative touch is the HI dual-motor electric driving system, which enables linked control and redundancy backup, preventing loss of power and ensuring driving safety. The system can also take advantage of AI and big data analysis to provide early warnings of battery exceptions, further improving driving safety.

Data safety and privacy concerns – a natural consequence of IoT – are also considered by Huawei, which has applied its experience in security to automobiles to fully protect users’ information.

Conclusion

Smart vehicles are the future of the industry as consumer trends continue to move towards it. With the technology still in its primal stages, it is a field as yet unspoiled, meaning the stakes for innovators and manufacturers are high. The target for firms looking to lead the digital revolution of the auto industry is twofold: safety and autonomy.

There are three key aspects to smart vehicles: smart manufacturing (for adaptability), AI (for efficiency), and IoT (for benchmarking progress). The latter is particularly important as we enter an unprecedentedly interconnected age, where the very act of changing gears on a highway sends data to the cloud and thereby informs decisions by tech companies and the algorithms on which they build their tech.

The use and application of IoT within the context of smart vehicle production is not without its challenges. The first is an ethical one concerning personal data and privacy. The second concerns engineering: how does one build the technology required for cars to be fully safe and autonomous? Our research demonstrates that a key solution is innovation not just on a technological level, but a structural level: traditional R&D models will have to be overhauled completely. Moreover, we expect to see an emergence in collaborative approach between different, highly specialised firms.

To illustrate this trend, we observed the solutional models developed by Huawei. Huawei edges ahead of the competition in each of the smart vehicle pillars (AI, smart manufacturing and IoT) with an innovative ‘platform + ecosystem’ development strategy, on which it is building an industry ecosystem based on partnerships between specialised tech and engineering firms. It is the success of these partnerships, and the network of information created through IoT, that will determine the course and progress of smart vehicle development.

In a world where everything is connected, smart vehicles will not only facilitate the experience of driving for consumers but allow physical and digital experiences to exist in symbiosis, using AI and IoT to drive us into a world of automated harmony.

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