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Trends and Innovation in AI and IoT

Automotive Industry

Written by Anonymous

Paper category

Essay

Subject

Business Administration>General

Year

2020

Abstract

Hausarbeit AI and IOT: Artificial intelligence and the Internet of Things are technological revolutions that have significantly transformed the business sector. The interrelationship between AI and IoT has had an immense contribution to the growth of the automotive industry from manufacturing to business operations in the sector (ATCC, 2015). This particular report explores how the automotive industry will exploit, implement and utilize AI and IoT for both their current business operations and future growth opportunities. The essay provides a historical perspective of the automotive industry in relation to the adoption and implementation of AI and IoT in their operations. Academic theoretical concepts and frameworks have been presented to offer an in-depth view on the topic. Challenges and gaps facing the automotive industry in the adoption of the mentioned technologies have been discussed. Also, the report provides insight into the category size and demand spaces of AI and IoT within the automotive industry. Finally, the report has provided an in-depth analysis of the new opportunities for AI and IoT for the automotive industry.The history of AI and IoT within the automotive IndustryThe concept of AI was officialized in the year 1956 at Dartmouth College while IoT was founded in 1962 by the Defense Advanced Research Projects Agency. The core reason for the establishment of these technologicaltools was to improve the efficiency of machines, business, communication, and life in general (Gusikhin, Rychtyckyj & Filev 2017). As advancements were made through research, the automotive industry gained interest and started to explore the field of AI and IoT to improve its services and products (ATCC, 2015). The two fields, AI and IoT are closely interrelated, Vermesan (2017) notes that the ultimate potential of IoT can only be made feasible through the integration of AI. Kevin Ashton coined the term with the vision of having a world that is connected both in communication and in contextual services. On the other hand, Minsky and McCarthy came up with AI intending to simulate human intelligence in machines for the machines inclusive of automotive machines to mimic human actions (Vermesan, 2017). The onset of the industrial revolution saw many automotive companies delve into the adoption of AI and IoT to enhance the efficiency of their products.Theoretical concepts and frameworkThe concept of AI and IoT has been there for quite some time. In the 1700s, for a long time, humanity has been fascinated with the concept of AI. One of the ancient Greeks ones imagined a giant by the name Talos, which is big bronze automation which was created to guard the Cretan town of Europa from invasion by pirates (Gusikhin, Rychtyckyj & Filev 2017). Also, Wolfgang von Kempelen created an artificial mechanical man by the name The Turk in the 1700s (Vermesan, 2017). According to him, the Turk was an artificial person who could play chess. Some robots have been designed with the ability to make cars that are driverless to some degree (ATCC, 2015). Even though there are still many things that should be done before human intelligence systems can be fully developed, there are varied automated machines within the automation industry that can partially exhibit human intelligence in their operations.Challenges/gaps automotive industry faces in adopting AI and IoT technologiesA major challenge facing the adoption of AI and IoT is the lack of skilled experts or rather professionals who have the knowledge and innovation skills to run the sector. Many automotive companies and research organizations are finding a hard time getting the right people to foster faster development with emerging technologies. ATCC (2015) notes that several challenges are hindering the adoption of AI and IoT within the automotive industry for instance lack of training on data and skills and the presently used legacy systems (Vermesan, 2017). Also, the sensors being used in cars are not sufficient in ensuring high degrees of safety thus there is a need for further improvement.On the other hand, even though the significance of adopting AI and IoT within the automotive industry has been ascertained, still the implementation of these technologies within the enterprise level is currently challenging. According to Gusikhin, Rychtyckyj & Filev (2017), the computing power of ECU’s is currently not available thus making implementation a big challenge within the automotive section. Furthermore, rules and regulations hinder implementation since the development, training, and validation of these technologies’ algorithms is against numerous technical and regulation policies (Aikaterini, 2014). Also, the lack of sound business models to monetize AI and IoT applications is proving to be a challenge in the utilization and implementation of these tools within the automotive industry (Vermesan, 2017). Additionally, there is the challenge of complying with prevailing stringent safety and reliability standards.Category size of AI and IoTNetscribesreport on the global market showcases that the international IoT within the automotive industry will grow by 27.55% and attain a market size of $104.16 billion come the year 2023 (ATCC, 2015). The compound annual growth rate has been estimated to stand at26% while efficiency needs in the processing of chunk volumes of real-time data that is released from these devices and minimize maintenance charges and downtime are the major driving factors (Özdemir & Hekim 2018). The machine language and deep learning technology sectors are the ones currently holding the largest market size. Regarding world regions, forecasts have revealed that North America holds the largest market size in both AI and IoT while Asia is projected to be the fastest-growing region. Some of the notable AI and IoT global vendors comprise Microsoft, Oracle, Google, SAP, Gitachi and Autoplant Systems Pvt Ltd among others (Vermesan, 2017). The currently available sectors in AI and IoT are platforms, software solutions, and services. On the grounds of technology, the ML, Deep Learning and NLP are the major segments. In terms of connectivity, the market size has been divided on the grounds of integration, embedded and tethered (Aikaterini, 2014).Demand spaces automotive industry needs in implementing AI and IoT technologiesSeveral demands must be fulfilled before the actual implementation of AI and IoT technologies within the automotive industry. Manual maintenance and supervision are some of the greatest challenges that must be met for effective implementation to take place since users and consumer data are in question (ATCC, 2015). Cross organizational comprehension is another demand for implementation of AI and IoT in automotive industries. Companies within this market ought to have outstanding experts who will understand the entire operations to identify challenges and provide solutions for effective implementation to be feasible (Vermesan, 2017). Solutions to legacy systems have also been noted as a demand space automotive industry should solve before the actual implementation of automotive vehicles and machinery. Regions where AI and IoT has been adopted in the Automotive IndustryAmerica, Europe, and Asia are considered to be the regions whereby the automobile industry has exploited, implemented and utilized AI and IoT in their current business operations. In America, companies such as nuTonomy are developing nutonomous technological vehicles that are intended to be entirely driverless (Vermesan, 2017). The company has its headquarters in Boston Massachusetts. Another company is the AutoX Company located in San Jose, California. The company uses Ai in the automotive industry by making retail-based autonomous vehicles. They have combined AI software, real-time camera and sensors to improve their cars and improve on-road safety both within the virtual and real worlds. Tzafesta's (2018) study shows that European nations such as Sweeden, France, Italy, and Germany have significantly adopted AI and IoT technologies which are expected to have agreat contribution within the fields of the automotive industry (Gusikhin, Rychtyckyj & Filev 2017). The forecast shows that the autonomous vehicles market in China will rise to around 1.5 million units in china. China’s FAW Group Corporation has been identified as the top automotive domestic automotive OEM concerning autonomous vehicle technology (ATCC, 2015). Apart from the mentioned regions, the other regions are still lagging in terms of the integration of AI and IoT in the automotive industry.New Opportunities for AI Automotive IndustryAutonomous driving has been a central concern for the automotive industry for quite a while. Most of the progress observed within the automotive industry has been drawn from the advancements within artificial intelligence technology. The applications that are being and will continue to be implemented within the automotive industry are not only limited to autonomous driving but also in learning and other business aspects within the industry (Vermesan, 2017). Research shows that the value of artificial intelligence within the automotive manufacturing industry and other sectors such as cloud services are estimated to surpass $10.73 billion in five years to come (Gusikhin, Rychtyckyj & Filev 2017).Automated vehiclesrelease a huge chunk of data. There are expectations that automated cars will generate nearly 4000 gigabytes in a single day. Due to this, there will be the need for the automotive industry to link with AI cloud platforms which will ascertain that all thegenerated data are available in times of need. Through the integration of the AI automotive industry and cloud services, the competition within the market will increase tremendously (Aikaterini, 2014). AI cloud services are effective in facilitating personal ads that are indispensable within the marketing filed (Gusikhin, Rychtyckyj & Filev 2017). Additionally, cloud services are integral within the automotive industry as they will eliminate the challenges associated with targeting qualified predictions. Since they are connected to big data and vehicle infotainment systems, they can thus be employed in making individualized recommendations to drivers (ATCC, 2015). The advantage of using AI is that it knows drivers and can make relevant suggestions basing onthe locations that the drivers will be at the time of order (Aikaterini, 2014). Moreover, AI is integral within the automotive industry as it aids in facilitating predictive maintenance. Currently, people find it easy to identity whenever car maintenance is needed. For instance, currently, vehicles notify drivers whenever there is a need to refill oil or even whenever it is required to check the functionality of engine lights. Artificial intelligence within the current automotive systems has taken the roleof monitoring all the sensors in a vehicle and detect any potential challenges earlier enough before the occurrence of a default (Vermesan, 2017). Car maintenance is easier nowadays because AI can easily detect changes that are associated with failure earlier enough before they can affect the proper functioning of a car (Tzafestas, 2018).In 2018, Volkswagen partnered with Microsoft allowing them to provide predictive maintenance and over the air software updates to users. This move by Volkswagen is a clear indication of the possibility and interest of the automotive industry to integrate automotive cloud computing in its operations (Tzafestas, 2018).Through the integration of artificial intelligence within the automotive industry, many advantages can be garnered. For instance, self-driving cars and driver assistance are the most discussed topics currently since their possibility has started to become evident. Aikaterini (2014) notes that there is a possibility of AI to make it visible for autonomous vehicles to be legally accepted within the mainstream mode of traveling and transportation. Also, the author notes that AI will in the future change many dimensions of the auto manufacturing processes ranging from research, design and even in project management especially in the aspect of business support purposes (Gusikhin, Rychtyckyj & Filev 2017). On the other hand, Vermesan (2017) asserts that the automotive industry is significantly impacting the society while the integration of technology within the automotive industry heightens efficiency is myriad ways. Currently, many automotive firms are spending a lot of time and their resources on the sectors which were neglected in the past. Many companies are currently implementing the concepts of AI and IoT in newly produced cars to gain an advantage over their competitors (ATCC, 2015). New Opportunities for IoT in Automotive IndustryThe Internet of Things, on the other hand, is significantly transforming the automotive industry. It's recorded that the automotive industry is one of the leading industries that are exploiting IoT through outstanding innovations currently being developed and implemented within the sector (Aikaterini, 2014). There are innovations in place within the automotive industry using IoT knowledge to develop standard cars that will transform from assisting drivers in taking control of the driving process entirely. Through the integration of IoT, it will be possible for cars to have sensors to identify and communicate with upgraded road signs via a network of cameras. ATCC's (2015) research shows that in the future, there is a possibility that vehicles will be carrying out numerous tasks that are currently being done by drivers. For instance, automotive cars integrated with IoT technology will have fuel trolls whereby drivers will not even have to pay for fuel since vehicles will be in a position of executing this function by themselves. Additionally, IoT integrated vehicles might even be paying for their insurance.Gusikhin, Rychtyckyj & Filev (2017) assert in their research that the integration of IoT in automation cars will enhance road safety. Vehicles in the future will have alert sensors that will detect things like bad driving and accidents on roads. Reports provided on IoT suggest that there are already invented devices that can automatically detect collisions and instantly contacting emergency services providing them with the location of the accidents (Gusikhin, Rychtyckyj & Filev 2017). These reports can also be given to automotive manufacturers so that they can make improvements to their vehicles. IoT can reduce if not eliminating accidents resulting from human error as they have the ability of monitoring driving habits and sending suggestions to respective drivers. Automotive firms in the United Kingdom are already taking advantage of this technology in their efforts to enhance the standard of driving for their employees and clients.Moreover, IoT can eliminate the challenge of traffic congestion in towns. The knowledge of swarm intelligence in traffic can make it feasible for traffic operators to coordinate cars making it easy to reduce congestion. IoT can check places whereby there are common checkpoints and categorize the time of day when there is traffic on the roads (Aikaterini, 2014). The availability of such kinds of information is integral as they can aid engineers and road experts to come up with plans that can be used to eliminate traffic during peak times or conditions. Moreover, IoT can be employed by automotive companiesto minimize pollution and energy expenditure. There are lots of information that can be drawn from IoT technology which can be employed in establishing greener solutions (ATCC, 2015). One of the cities that has shown immense progress in the use of IoT within the automotive industry in Singapore. Singapore has done an outstanding move in implementing congestion charges and putting more investment in installing road sensors, smart packing lots and phased traffic lights (Vermesan, 2017). These IoT technologies have enabled Singapore to enhance the concept of greener smart cities by reducing toxic gas emissions. Furthermore, in Jamshedpur, India, IoT integrated streetlights that are employed in tracking movement on the roads to determine when the light is required. This particular technology has helped the region in saving on needless electricity consumption.ConclusionIn conclusion, both AI and IoT have significantly impacted the automotive industry in myriad ways including the industry’s business transformation. There are numerous opportunities that AI and IoT have brought to the automotive industry. For instance, through AI, automotive industries currently can predict maintenance, providing recommendations to drivers and saving time and resources. In the future, vehicle companies might make driverless cars which will have a significant impact on society. This will be possible through the integration of IoT. Business-wise, IoT has significantly contributed to effective and efficient marketing. However, there are still challenges hindering the anticipated progress, for instance, dealing with the law and regulations and lack Read Less