Understanding the Convergence of IoT-AI-AR for the Industrial Sector
Adoption of the Internet of Things (IoT) in public and private organizations has grown strongly during the last decade with no end in sight. Today, IoT applications are becoming increasingly ubiquitous, touching every aspect of life and business – from manufacturing to retail to smart cities. However, challenges remain in the effort to accelerate IoT adoption and bring it to a more refined level of development.
Currently, IoT applications are primarily focused on using IoT devices to monitor and control spaces. The next steps in the evolution of IoT should be to be able to predict events and conditions, prescribe actions and automate the processes with the necessary balance between cloud and edge activities. This needs to happen in a secure manner, ensuring scalability and maximum efficiency while maintaining a continuous focus on business values all along the IoT solution lifecycle.
In all this, there is also a need to enhance the interaction between those intelligent spaces and the people who work within them. To do all that, the IoT needs to work together with other technological frameworks. These include:
- Artificial Intelligence (AI) to produce the right intelligence based on data gathered;
- Distributed Ledger Technology (DLT) to support trust and decentralization;
- 5G to enable different connectivity applications and performance depending on needs; and
- Augmented Reality (AR) to create a conducive relationship between humans and intelligent spaces.
This article will briefly illustrate the work being done within the AREA on the convergence of IoT, AI, and AR.
The AREA – An Innovation-Driven Alliance
The AREA represents more than 60 members – AR solution providers, enterprises implementing AR, and non-profit institutions – dedicated to the adoption of AR in enterprise environments. The alliance supports its members in a variety of ways, including a continuous flow of market and technological research. The AREA’s member-funded research activities tackle key issues related to the implementation of AR in enterprises. In the first half of 2019, I began working with the AREA to address the convergence IoT-AI-AR.
The Reasons for the Convergence and the Architectural View of It
The research aims to understand the convergence of IoT with AI and AR in strongly process-oriented organizations, such as manufacturing, oil and gas, mining, and energy. Starting from the assessment of the status quo of IoT, the research found that AI and AR together can address some of the limitations and issues of IoT, enabling manufacturing companies to solve some of their key problems, such as inefficiencies in the use of resources and downtime. Based on the architectural framework illustrated in Figure 1, the research explored the technological components of the convergence and the community of players involved in developing it.
Figure 1: Architectural Framework for the Convergence of IoT-AI-AR (source: AREA).
In the architecture proposed, the complexity of an IoT solution made of devices, connectivity, and an Industrial IoT platform is increased by the addition of an Industrial AI/Machine Language platform and an AR platform.
Successful Proofs of Concepts Are Creating Momentum Around IoT-AI-AR
Despite the architectural complexity, the research (based on extensive interaction with vendors and adopters) revealed strong enthusiasm within an IoT-AI-AR community still in development and, sometimes, surprisingly disconnected. Successful proofs of concepts are driving that enthusiasm and creating momentum around the theme. The proofs of concept affirm the hypothesis of this research: that the convergence of IoT-AI-AR successfully addresses important manufacturing problems and enhances the potential of an IoT deployment in an industrial setting.
Organizational and Market Challenges Are the Major Concern
Despite the successful projects, the adoption of IoT-AI-AR-based projects is still at an early stage. There are technological challenges to overcome. The IoT-AI-AR community is less worried about technology and more concerned about the business and organizational implications of introducing those technologies in the enterprise.
For example, there is a common view that the current lack of AR device choices is a challenge, but there is also the confidence that this challenge will be solved within two years. Another issue is organizations’ data readiness to run ML algorithms for predictive solutions, but again, the community is convinced that the situation is improving and soon several organizations will be ready for ML in cloud and edge environments. Even on the security side, despite being a top concern, the community is confident in its maturity.
But that confidence diminishes when the issue becomes more organizational and business-oriented, such as the perception of privacy and control among workers wearing AR devices or developing business models for the enterprise when the current AR business models are tailored for the consumer market.
Changing the Narrative Around IoT-AI-AR and Reinforcing Collaboration Through Ecosystems
It appears that the community is bound by its shared trust in technological progress but disconnected on the rest of the issues with no answers to address them. That disconnection is slowing the speed of adoption even though the proofs of concepts demonstrated that the convergence of IoT-AI-AR can solve manufacturing companies’ issues and introduce new and better ways of working. Considering all this, the conclusion of the report almost put aside technology, trusting in the extraordinary innovation capabilities of the community, to instead focus on some key organizational and business messages. Among them, there are two important messages to highlight:
- The narrative around IoT-AI-AR is a narrative of fear, the fear of automation and of the loss of any role for humans. This narrative is wrong and needs to be overturned. The convergence of IoT-AI-AR, like other technological developments, is being explored to solve problems, to reduce the role of humans in dangerous activities, and to enhance their working roles to allow for more intellectual activities. That change of narrative needs to come with a strong educational program.
- The convergence of IoT-AI-AR will come only when IoT-AI-AR ecosystems are formed. Innovation and market collaborations become essential for overcoming the challenges discussed.
Conclusion – Inter-Alliance Collaboration Will Help Advance IoT-AI-AR Convergence
The report, available exclusively to AREA members, begins to shed light on the potential applications and benefits of IoT-AI-AR convergence. There is much more to explore. That work should be done collaboratively between consortia and alliances involved in the three technological frameworks. Bringing together the AREA and alliances from the worlds of IoT and AI in a dedicated working group can help drive the development of IoT-AI-AR ecosystems, stimulate cross-discipline debates, promote best practices and tools for the design and development of IoT-AI-AR projects, and articulate a new language that positively and inclusively describes the scope of the convergence.
Saverio Romeo is Associate Lecturer at Birkbeck College on emerging technologies (IoT, blockchain, and AI) and their impact on innovation and policy. He runs modules for postgraduates and undergraduates on emerging technologies and contributes to research activities on the impact of technologies in business and society. He has almost 20 years of experience in M2M and the IoT in various positions, from analyst to adviser, from telco engineer to technology policy consultant.
Mark Sage is the Executive Director of the Augmented Reality for Enterprise Alliance (AREA). The AREA is a membership funded alliance, helping to accelerate the adoption of Augmented Reality (AR) through a comprehensive ecosystem. With a focus on creating value and ROI for its members, his goal is to develop a robust and active ecosystem for AR. His background includes a strong interest in mobile, AR, VR, and IoT and he is excited to work with enterprises, providers and research organizations to the benefit and growth of the AR within the enterprise.
Sign Up for IoT Technical Community Updates
Calendar of Events
2020 International Conference on Recent Advances in Intelligent Computational Systems (IEEE RAICS 2020) - Virtual
4-5 December 2020
2020 IEEE Global Conference on Artificial Intelligence and Internet of Things (IEEE GCAIoT 2020) - Dubai, UAE
12-15 December 2020
IEEE IoT Vertical and Topical Summit at RWW 2021 - Virtual
11-16 January 2021
Call for Papers
IEEE World Forum on the Internet of Things (WF-IoT) 2021
Submission Deadline: 15 January 2021
Special Issue on Information-Centric Wireless Sensor Networking (ICWSN) for IoT
Submission Deadline: 15 November 2020
Special Issue on Connected Smart Sensors Systems for Water Quality Monitoring
Submission Deadline: 1 December 2020
Special Issue on M2M/IoT Services over Satellite Networks
Submission Deadline: 15 December 2020
Special Issue on Secure Data Analytics for Emerging Internet of Things
Submission Deadline: 1 January 2021
Special Issue on Security, Privacy, and Trustworthiness in Intelligent Cyber-Physical Systems and Internet-of-Things
Submission Deadline: 15 January 2021