iCrowd Newswire – Sep 17, 2020
The autonomous decision making process involves data extraction mechanisms and tools such as data mining, machine learning, and statistical modeling to analyze data, identify significant patterns, and make probabilistic predictions for business intelligence.
Decision making is a manual process, where an individual or group is involved in simultaneous consideration of a lot specific and general factors, such as managing, evaluating, and analyzing the raw data. It is difficult to determine the accuracy, consistence and correctness of the background knowledge applied in the manual decision making process. Thus, it is difficult to assess the accuracy and efficiency of the final decision. Autonomous decision making systems involve gathering, storing, and processing of information to improve the quality and consistency of the decision making process and making it more intelligent straight through processing.
For autonomous decision making scenario, we have considered a convergence scenario where six different technologies converge to provide an autonomous decision making in different environments.
Smart Sensors: Smart sensors possess capabilities beyond merely detecting certain parameters and sending raw uncompensated signals. Smart sensors with appropriate communications capability can be easily implemented in a network of sensors for efficient communication.
M2M Communication: M2M is a technology that allows two or more intelligent machines to communicate with each other through a communication network and without human intervention. Once the data is transmitted through the network, it is collected for analysis and assessed properly to extract essential information.
3D Printing: 3D-printing technology is a type of layered, additive manufacturing process that is being used to manufacture parts without any specialized tools.
Big Data: Big data refers to a collection of complex and large-scale data sets. Big data technologies include storage components, processing capabilities, and applications that have been developed to handle large volumes of data.
Predictive Analytics: Predictive analytics allows obtaining actionable intelligence from a wide range of data sources obtained from sensor fusion to predict about future trends and probabilities.
Context Aware Computing: Context aware computing software has the capability to examine and react to an individual’s context change such as brain computer interface. It can sense the user’s state and surroundings and can seamlessly adapt to the behavior of the users.
Automotive: Companies in the automotive domain are developing collaborative automated robots in engine production plants. The collaborative robots will be working with people, carrying out physically demanding tasks in the engine assembly process. To prepare themselves for future growth, a lot of automakers, including Audi, BMW, Mercedes-Benz, Nissan, and Volvo, are developing autonomous self-driving cars with the help of autonomous decision making systems which will monitor the environment and take accurate decisions.
Aerospace: 3D printing is gaining traction in aerospace and defense industry. It is used to manufacture prototypes of aircraft wings and engine components. Companies are employing predictive analytics to identify operational issues faster with 3D printing. Companies are developing robots with the help of 3D printing and predictive analytics which can function autonomous without human intervention.
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Several parallel efforts are in progress in predictive analytics to identify and mitigate the operational issues faster in 3D printing. 3D printing is used to develop sensors, and prototypes of several different products. With ongoing developments, 3D printing will greatly enable autonomous decision making platform solutions. Autonomous decision making is developed not because the technologies are mature, but in response to business needs, such as increasing consumer expectations, data flow and cost. To enable decision making process, smart sensors are employed to detect and report the physical phenomenon and collaborate with other platforms for communication and knowledge sharing. Big Data, predictive analytics, and context aware computing demonstrate data architecture and define the way in which data is first collected, stored, then aggregated, and shared throughout an organization. Depending on the complexity and type of work, appropriate tools are employed. Due to the degree of interdependence, it can be expected that there would be a considerable overlap in the choice of technologies, such as context aware computing, brain computer interface, gesture recognition, sensor fusion and predictive analytics. Collaboration of tools will enable communication and knowledge sharing. .
High Growth Opportunity for technical advancement
By employing technologies such as big data, predictive analytics and context aware computing, companies will be in a good position to contribute to the market growth. Cost-efficient solutions, such as smart sensors and 3D printing will increase the brand competitive strength. The adoption of the ICT solutions is also expected to increase. Opportunities and technology procurement in North America and Europe will remain high because of the government support which influences plan for intelligent decision making in manufacturing. North America and Europe will have high opportunities fueling the growth of autonomous decision making market.
Smart process applications is one of the key methods to drive the autonomous decision making market in the manufacturing and energy industries. In addition, it will provide opportunities to major market participants in smart grids and automotive sectors in the coming years. Total spending on context aware computing and predictive analytics is expected to increase, but the growth will be slower in 3D printing and other technologies due to the existing assets and longer life times.
USA: Autonomous decision making is increasingly adopted for its ability to act as a system interface for human thinking and cognition. In North America, the major sectors that adopt automated decision platforms includes automotive, industrial, and energy. The USA will be the largest market for autonomous decision making in the medium-to long-term. The M2M cloud platform, 3D printing, smart sensors, predictive analytics and context aware computing are gaining traction. The convergence scenario will lead to creation of new revenue streams.
Europe: The European Commission is key to promoting predictive analytics in the region. Its recent collaboration with Capgemini to develop a Pan-European Big Data platform will allow European citizens to have access to any public data in over 39 countries. The platform will enhance collaborative efforts in predictive analytics through European innovators. Several start-ups such as Viscovery and FutureLytics are emerging with innovative smart process specific applications to meet the demand for intelligent decision making platform solutions in this region
Asia-Pacific: Predictive analytics is in close competition with global innovation landscape. Companies from China and Singapore are emerging with various new applications to meet demand in this market. Various Indian start-ups such as Flytxt, Formcept, and Crayon Data are also emerging to compete in the global market as well as meet the analytics needs in the Indian market. In Asia, context aware computing is adopted majorly by electronic display companies.
The market is currently in the growth phase and it will be driven because of the real-time evaluation and utilisation of the high volumes of data created in the value chain. In addition, autonomously organized production will efficiently and quickly deal with fluctuations in production.
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Keywords: Technology Convergence,Automotive,Sensors,straight through processing, brain-computer interface, gesture recognition, sensor fusion