## 1 Introduction
### Decentralized Mobility Solutions  
In this section, we compare and contrast two decentralized mobility data solutions already in production with a modest market share thriving in an ecosystem of partners for offering \"Return on Data\" shared with these networks.  
* Digital Infrastructure for Moving Objects (DIMO): [3] It is a data-driven decentralized public IoT platform that requires the vehicle owners to install an AutoPi telematics unit in their vehicle, which then submits the data at frequent intervals to the cloud infrastructure. Its infrastructure comprises the Polygon Blockchain, the Inter-Planetary File Storage (IPFS) decentralized storage, the Helium decentralized LoRaWAN wireless network and other additional protocols. Users can submit their data and can gain DIMO tokens as rewards. The platform then utilizes the collected data for receiving recommendations on preventive vehicle maintenance, service history, and other sensor records. The shared data are then sold to aggregators who reward and incentivize the DIMO network and vehicle owners. The compromise we notice with this system is that the data life-cycle is questionable regarding its provenance, destruction, obfuscation by removing sensitive details and the overhead of installing a device for protocol communication. Though the vehicle Users and OEMs monetise their raw data directly they lose the opportunity by failing to enhance the data and build services on top of it which might increase their revenue. Although it is designed to solve the problems of data centralization and privacy concerns, it needs more analysis, as the data are stored by centralized actors in the ecosystem.
* Ocean Protocol: The Ocean Protocol [4] is a data marketplace built on the parity Ethereum Proof of Authority blockchain protocol. It is a decentralized data exchange where individuals or enterprises exchange the data shared as ERC721 data NFT tokens by Ocean smart contracts. Then, ERC20 data tokens are generated for the data service to access the published data for a dynamic or fixed price. The existing use cases generated are for connected living, where the elderly patient's data are shared for customized insurance and medical assistance. Also, the health data for heart condition patients are shared with Roche Diagnostics from a CoaguChek IN Range device to the ocean protocol, enabling data discovery for other third-party partners offering medical services. Also, a data NFT can be marked as purgatory or unusable if there is an issue with data privacy, quality or copyright infringement. To preserve the confidentiality of the data, the marketplace offers compute-to-data, where instead of the data transfer, the buyer of tokens can obtain the pre-computed trained data model to be used, and the raw data stay in the storage of the data marketplace. This protocol is quite comprehensive with no additional hardware requirements, but there is a problem with the data certification, as data shared can be tracked for their provenance. Still, data quality and genuineness are pointers to be considered by them as anyone can share data and earn tokens without pre-emptive checks.  
Our data-monetization architecture solves the concerns mentioned above regarding data provenance and certification using a streamlined data flow with no additional hardware required. It also ensures the privacy of the data within a consortium blockchain of agreed and verified partners with mutual benefit for everyone in the network.