WiMi builds enterprise data management system WBM-SMEs based on blockchain, AI, IoT
WiMi Hologram Cloud Inc, has announced development of a data management system for SMEs. This combines blockchain, AI, and IoT technologies to help companies achieve efficient, collaborative and intelligent processing of data.
In the era of Web 3.0, SMEs are facing many challenges at the same time. For example, the current distributed data management platform is designed for SMEs. The data collaboration and linking ability between platforms is low, making it challenging to ensure data accuracy, integrity, and reliability for enterprise operations, thus leading to low data management efficiency and insufficient data utilisation. In addition, data encryption protection and anti-tampering also need to be significantly improved. Most of the current data management in SMEs is based on a centralised server management model. This also makes data collaboration and data trust between two different enterprise partners problematic.
The reason for centralised management of enterprise database infrastructure is also based on enterprise data security, privacy, and data extraction efficiency, and it is a necessity. Therefore, improving enterprise efficiency and productivity through data lightening and intelligent analysis and revitalising static data is the core issue of enterprise data management. Based on this, WiMi develops a smart collaboration system for data management for SMEs so enterprises can efficiently link collaborative work in Web 3.0, and enterprise data can be efficiently utilised and processed anytime and anywhere.
WiMi uses blockchain, IoT, AI, and machine learning to propose a novel and efficient security framework for distributed SMEs with standardised processes, hierarchies, and task life cycles. The WBM-SMEs system is based on a blockchain with a permissionless network structure supporting the IoT, providing a solution for cross-chain platforms. The system also solves the authentication problem among lightweight partnership partners. For this purpose, the system deploys three different chain codes.
It handles the daily information management of participating SMEs and exchanges between nodes, analysing transaction details related to the exchange before saving the blockchain’s immutable storage. The system uses an AI artificial neural network based on machine learning to process and optimise the number of daily transactions of SMEs. As a result, the WBM-SMEs system consumes fewer resources in terms of computing power, network bandwidth, and data preservation-related aspects, increasing the speed of ledger management and optimisation when exchanging information between different chains.
WiMi’s WBM-SMEs system offers several advantages in enterprise data and process management:
Efficient and analytical: The system provides efficient collaboration between customers and enterprises. For example, the interlink between manufacturing, production, and R&D includes data collection, management, and optimisation. The system enables the collection, organisation, and analysis of digital technology through artificial intelligence, helping companies to improve efficiency and provide detailed and favorable analysis.
Data security and transaction transparency: Standard processes and a secure, tamper-evident hierarchy guarantee transparency and authenticity of the information. The WBM-SMEs system, a distributed framework supporting blockchain and AI, provides a platform for users to design, create and deploy DApps to enable a transparent transaction environment. The system can automatically analyse and process the processes related to SMEs, especially transaction verification and validation, facilitating resource sharing between the two sides of partnership transactions.
Data and service lightweight: A distributed public permissionless network with blockchain integrated with AI technology provides a lightweight authentication mechanism that can reduce the cost of computing resources, network bandwidth, and storage.
The framework of the WBM-SMEs system is an AI-enabled, integrated blockchain divided into three distinct parts. The first is an IoT designed to collect, inspect and analyse SME-generated data or transactions. After proper checks, the system develops a schedule for data transmission through the wireless sensor network and manages daily transactions. Secondly, the AI part was split into two parts, the computational resource management and the neural network algorithms supporting the AI. A lightweight authentication is designed to provide an automated ability to grant access to each application request after a DApp has authenticated it.
New SMEs or corresponding registrations are processed using a Blockchain Distributed Ledger Expert. The BDLE is responsible for initiating further registration validation after a complete analysis of the incoming request and allows creating of in-chain transactions and exchanging details. AI-enabled machine learning algorithms are used to manage and optimise the data. The process discards duplicate data/transactions and organises logs sequentially while reducing computational resource consumption and preservation load. Third, blockchain permissionless public networks (peer-to-peer networks with interconnected nodes) are deployed with two communication chains: off-chain and on-chain. These two designed communication channels handle multiple transactions occurring in the chain, e.g., application requests, node-to-node activities, operational control, external communication, and information exchange, and internal transaction requests received on-chain for hidden processing.
On the other hand, off-chain communication handles all explicit activities (off-chain/cross-chain platforms). The main goal of the blockchain transaction processor is to schedule the list of transactions provided by external computation and execution. The computational load is reduced by calculating the hash of individual transactions in the WBM-SMEs system. And the InterPlanetary File Storage System is used to store a log of individual transactions in the chain in WBM-SMEs. The aim is to use this distributed immutable storage because it provides a book-keeping facility at the lowest cost compared to other distributed storage. The main reason for using it is that it allows scalability and cost-effective hierarchy in a distributed manner.
WiMi’s system has developed a classification mechanism for data management and optimisation that checks for redundancy in SMEs’ data/transactions and extracts the original data while discarding duplicate items in a pre-validation process. This process facilitates computational resource management to reduce computational costs and submits validated data in the ledger for further processing. In the context of analytic ledgers, the implementation of ANN technology addresses data management, organisation, and optimisation.
The technology can identify several new vulnerabilities in the distributed data management environment, such as data/transaction detection issues and unstable identification of files in different nodes. To analyse these problems, WiMi uses machine learning to build a data identification mechanism and associates it with ANN. It can efficiently extract models, detect, identify, and classify data files and transaction information from SMEs, and connect with ANN to schedule logs for processing while minimising the risk of data capture/loss by providing a sizeable dimensional space for classification.
Today, enterprises are highly dependent on digital management. In the era of Web 3.0 and more efficient links, SMEs face many challenges and new opportunities for their development. WiMi’s WBM-SMEs system combines blockchain, AI, and IoT technologies to create a data management system for SMEs that are encrypted, tamper-proof, secure, convenient, lightweight, and intelligent. The system will empower SMEs to enter the Web 3.0 era, improve efficiency and productivity, and provide enterprises with more efficient and intelligent digital management capabilities.
Comment on this article below or via Twitter @IoTGN