Dor uniquely combines blockchain with AI for anonymized, real-time retail traffic analysis. More
Fully Diluted Valuation | $1.49M |
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24H Trading Volume | $109,140 |
24H Low / High | $0.00 / $ 0.01 |
Circulating Supply | 307.50M |
Total Supply | 429.49M |
Max Supply | ∞ |
Categories | Smart Contract Platform 1 more |
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Founder | Anonymous |
Website | docs.getdor.com Whitepaper |
Socials | 1 more |
Explorer | Getdor 2 more |
Name | Pair | OG Score |
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Dor introduces a novel approach to retail analytics by combining the power of blockchain technology with artificial intelligence, aiming to transform how retail traffic and consumer behavior are analyzed. Here's an in-depth look at what Dor brings to the table:
Project Overview:
Dor's primary offering is the Dor Traffic Miner (DTM), a device designed to collect foot traffic data:
Foot Traffic Analysis: The DTM measures real-time foot traffic in retail environments, providing insights into consumer behavior patterns without infringing on personal privacy. This data is invaluable for retailers to optimize store layouts, inventory placement, and marketing strategies.
Blockchain Integration: By leveraging blockchain, Dor ensures data integrity, transparency, and security. The data collected is anonymized and stored on a decentralized ledger, making it tamper-proof and accessible for analysis while respecting privacy standards.
AI-Powered Insights: The Dor Metagraph, running on the Hypergraph, uses AI to interpret the collected data. This AI engine can predict trends, offer real-time analytics, and provide actionable insights to retailers, enhancing decision-making processes.
Token Utility: The $DOR token is integral to the ecosystem, used for transactions within the network such as paying for data mining services, rewarding participants, or as a stake in the system for governance or additional benefits.
Use Cases:
Retail Optimization: Retailers can use the insights from Dor to improve store operations, understand peak times, optimize staff allocation, and enhance customer experience by tailoring in-store environments based on traffic data.
Marketing Insights: The data can help in crafting marketing strategies by identifying consumer patterns, understanding dwell times, and tracking the effectiveness of in-store promotions or displays.
Privacy-First Analytics: Dor provides a solution for retailers who wish to gather data without compromising consumer privacy, adhering to data protection regulations like GDPR.
Community and Developer Engagement: Developers can build applications on the Dor network, using the data for various business intelligence tools, enhancing the ecosystem's utility.
Technological Framework:
Dor's system is built on the Hypergraph, which is envisioned to be more efficient for the kind of data processing required by Dor. This framework allows for:
Scalability: Capable of handling the large volumes of data generated by physical retail interactions.
Decentralization: Ensuring that no single entity has control over the data, reducing the risk of manipulation or bias.
Interoperability: Facilitating integration with other systems or blockchains for broader application.
Dor uniquely combines blockchain with AI for anonymized, real-time retail traffic analysis.
Information on the founders of Dor is not available.
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