Inspiring Data-Driven Business Models Based on 3D Vision

A deep Insight into Business Models based on Data, and How 3D Technology Helps to Create Innovative Business Cases in Disrupting Industries - Like Dr. Christopher Scheubel Showed at the Embedded Vision Summit in Santa Clara.

Typically, traditional Business models evolve from the current state of technology; these business models manifest themselves and pay the rent of the entrepreneur. When a technological disruption occurs, the process starts over again. In the current age of data, these disruptions happen continuously. Blockbuster and Netflix, record labels and Spotify, or LinkedIn versus other well-established personal services providers are perfect examples to learn and transform the knowledge - how data collected from 3D imaging can create new business models and disrupt nearly every industry.

Chris_kleinA business model essentially dictates how an organization creates value and delivers this value to its clients. Gaining a competitive edge from manufacturing industrial goods or raw materials is based on a specific technology or production process. Customers pay for a certain technology or goods; companies entering the market encounter hurdles in copying or improving upon the technology or product. The world of data is different. Technology opens opportunities, but soon commoditizes itself; therefore, its ability to provide a competitive edge is limited. Great databases are created while applying innovative technologies to the world of data, enabling data to be the basis for building enhanced user experiences. The data can create new business models with many advantages for companies over many decades. Competitive advantages based on data will be much more sustainable than the competitive advantages that are based on technology or production processes. Currently, corporate winners like Netflix, Spotify or LinkedIn, achieve and maintain their edge based on user data.

How 3D Technology Can Change Business

Depth information is created by different technologies including Laser, Stereo-Vision, Multi-View, or Time-of-Flight. The current disruption is not the technology itself, but rather the economics of the technology. Raw 3D data in the form of depth maps, point clouds, and voxels can be employed in methods needed for upcoming applications.

Consequently, many applications are fundamentally enabled, or can be partly enhanced by 3D technologies. The question is, where are the market trends going? Yole Développement, a market research and strategic consulting company, forecasts a compound annual growth rate (CAGR) of almost 40% in the 3D vision market. This forecast indicates a huge technological opportunity, and 3D offers the potential to enhance all industries. Most of the absolute growth comes from the consumer sectors like automotive, white goods, cell phones, and home devices. Vacuum cleaners use 3D for navigating in home environments; accurate depth information at very low prices enables this 3D technology for consumer devices. In addition, a large portion of this growth is predicted for the industrial and commercial field, where 3D is implemented for process surveillance or robot guidance; people counting applications for stores; public buildings; and, public transport. An already existing potential lies in industry 3D applications where it supervises production processes. Control posture and gesture recognition applications are new drivers in sports and entertainment. There is a huge potential for creating new business opportunities with 3D data and data-driven business models, in the near future.

How to Create a Database for a Competitive Edge?

Data is a valuable commodity; but, how can its potential can be realized? In a logistics project that FRAMOS is involved in, a robotic system is devised to unload sea freight containers. The robots use both 2D and 3D vision to handle items in a container. In addition, semantic segmentation determines the edges between the boxes.

A 3D camera determines how the robot shall approach and manipulate the item in the container, thereby creating a database about both the container and its contents. System performance based on this database increases tremendously, and virtually any item can be unloaded without error. In addition, reinforced learning is possible, as there is feedback about whether the unloading process worked adequately, or if there were process issues. Different business models using this data are possible: the carrier could be charged for the way the container is packed, for example, and the degree of automation that can be applied to the unloading process. If there is enough perspective on containers, even a business model based on the amount and types of goods that flow through unloading facilities appears to be realistic. Therefore, information about which goods and where they are shipped can be applied to market-based pricing.

Palette_1_3d_4-kleinPicture 2: Pallet in 3D   

Another example is the 3D technology that self-driving cars, drones, and other types of robot rely on to navigate autonomously. Simultaneous localization and mapping (SLAM), a methodology by which 3D maps enable autonomous vehicles to navigate within their environment, provides completely new business opportunities. The accumulated 3D data not only increases the robustness of the SLAM algorithm and the accuracy of the system, it is a valuable resource with which to create a competitive edge.

Three dimensional maps of the world – inside buildings and out – can be created instantly providing innovative approaches to existing businesses. For example, some consumers still spend large sums of money on a vacuum cleaner robot. In the future, they could save a lot of money with leasing models that include the potential for targeted advertising. The intelligent and IoT networked vacuum cleaner would be able to identify the exact size of the apartment; the floor plan; the brands and the condition of the furniture; and, the individual furnishing styles. This data would allow conclusions to be drawn about the level of the owner’s income, and, with the appropriate consent, provide individualized advertising. A furniture store, for example, can propose a couch to potential customers that matches the desired dimensions, style, and the price based on their lifestyle. These data-based models would favour the purchase of this type of vacuum cleaner, because the manufacturer makes their profit based on the sale of data. In addition, it is conceivable that customers could lease these vacuums on a per-use basis and receive advertising accordingly. It is important to remember one hypothesis from 2017’s Embedded Vision Summit: 3D maps of the world in the future will be much more valuable than Google Maps today.

Think: Data

Companies wanting to benefit from 3D vision and brainstorm ideas on future business opportunities in disrupting markets, have to think thoroughly about their processes and applications. Is there a way to enhance or enable the existing applications using 3D technology, with corresponding methods like SLAM or object recognition?

This can be the premise for a powerful database with which to establish a competitive edge. Most likely, it will be the basis for AI, which uses large databases.

Managers should think about the kind of data that can be collected and how it can be used. These steps are the foundation from which to develop promising business models using 3D data, and maintain a competitive edge along with creating even more useful data.

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