A Framework for Understanding the New Transport Value Chain

October 17, 2018


By Vangelis Andrikopoulous and Lawrence Lundy Bryan

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In our latest report on the impact of converging technologies such as blockchains, IoT, and AI we take a closer look at the transport industry. To download the full report now click here. This post provides a high-level view of our findings and explains why the convergence framework is a valuable tool to understand the disruption taking place in the transport sector today.   


The shift to Open Mobility

The transportation and logistics value chain has been fixed for decades as oil and gas companies provided the energy and energy infrastructure with auto manufacturers producing, distributing and selling vehicles via dealerships. It was a symbiotic relationship that has served all parties very well. But all good things must come to an end, and so it is with the transportation and logistics industries. Energy sources are diversifying, customer purchasing motivations and behaviours are changing, and technology is changing the very experience and job-to-be-done of transportation.


The open mobility value ecosystem of tomorrow incorporates renewable energy sources turning consumers into prosumers capturing, storing and exchanging energy on decentralized transactive grids. As vehicles become computers on wheels, data will unlock new economic value and data-driven business models. Drivers decline, fleet operators proliferate, tokenized sharing economy combines with integrated multimodal mobility-as-a-service.


We view these transformations through the lens of the Convergence ecosystem framework which sees data as the resource to be produced by sensors connected to the Internet of Things, distributed by blockchains and other crypto-networks, traded in marketplaces and consumed by artificial intelligence. We believe without this framework, the industry is destined to be reactive and lose the vital customer relationship and prime place in the value chain to software companies.  

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Data collection

The foundation of the convergence ecosystem is based on data collection which is enabled by the internet of things, software, operating systems and applications. While sensors embedded in hardware will capture the external environment, software, operating systems and applications capture a constant feed of data from internal processes such as in-transit interfaces and mobility-as-a-service platforms. Vehicles become autonomous economic agents and value will derive from the broader aggregation of data.

Case study: FOAM protocol

The aim is the development of geospatial blockchain protocols and standards for location encoding, map UI, and proof of location. The FOAM Proof of Location protocol empowers a permissionless and autonomous network of radio beacons that can offer secure location services independent of external centralized sources such as GPS through time synchronization.


Authentication, validation and security

Distributed ledgers and blockchains provide a mechanism for the transaction, verification, and storage of digital assets such as digital twins of vehicles, OEM parts and user credit for mobility-as-a-service platforms on distributed ledgers. Access control networks like Xain can allow for the secure sharing of mobility data. Vehicles and users can have a self-sovereign ID that enables them to access services securely and seamlessly.

Case study: Sovrin

Sovrin is a decentralized, global public utility for self-sovereign identity. Self-sovereign means a lifetime portable identity for any person, organization, or thing. Having a self-sovereign identity allows the holder to present verifiable credentials in a privacy-safe way. These credentials can represent things as diverse as an airline ticket or a driver’s license.


Data transport and routing

After data has been authenticated, validated, secured and stored it will need to be transported. Interoperability protocols are being developed for messaging, value, data and state. Cryptographic tools provide increased privacy controls for network participants. Data and value becomes interoperable and flows seamlessly across blockchains.

Case study: Haja Networks

Open-source protocol to build decentralized databases that enable users to own and control their data and that can be integrated with existing database systems. Haja is currently developing OrbitDB, a scalable and trustless peer-to-peer database that enables cryptocurrency based marketplace for decentralized cloud-database services and database providers to monetize their software as a service.


Data marketplaces

The vast amounts of data being collected constitute the foundation of decentralized marketplaces. Decentralised AI data marketplaces, personal, internet of things and digital asset markets will reduce, and eventually remove, the competitive advantage of hoarding private data by enabling anybody to monetize data.

Case study: Ocean Protocol

Ocean Protocol is an ecosystem for sharing data and associated services. It provides a tokenized service layer that exposes data, storage, computes and algorithms for consumption with a set of deterministic proofs on availability and integrity that serve as verifiable service agreements. A multitude of data marketplaces can hook into Ocean to provide “last mile” services to connect data providers and consumers. It’s designed so that data owners cannot be locked-in to any single marketplace. The data owner controls each dataset.


Process, analyze and automate

Decentralized machine learning can transform raw data into actionable knowledge; converting voice input into text output in voice-to-text programs that can be used in in-transit user interfaces or turning LIDAR input into a driving decision for autonomous vehicles. Smart contracts and distributed computation enable transparency, security and seamless communication between fleet operators, automotive and original equipment manufacturers, service providers and users.

Case study: Fetch.AI

Fetch is the world’s first adaptive, self-organising ‘smart ledger’. Useful economic activity is performed by Autonomous Economic Agents (AEAs). These are digital entities that can transact independently of human intervention and can represent themselves, devices, services or individuals. Agents can work alone or together to construct solutions to today’s complex problems.


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