Rayvo
  • Welcome
  • Sight in
    • What is Rayvo
    • What We Solve
    • Get Started
    • Why Rayvo Leads
    • What is SightFi?
      • Value of Data
      • Digital Identity
      • Cryptocurrency Payments
      • Multi-Dimensional Data(POV Data)
  • Potential and Edge
    • Rayvo Protential
      • Unique Value Proposition
      • Broad Application Scenarios
      • Early Adopter Advantage
  • Products Introduction
    • Smart Glasses
    • Rayvo One
      • Features
      • Product Parameters
    • Rayvo Companion App
    • Data Refracter Lens
    • Genesis Data Refracters
    • Ring: Rayvo Ecosystem Component
  • Busiess Model
    • Key Pillars of the Business Model
    • Core Value Proposition
  • RoadMap
    • ROADMAP
  • Token Introduction
    • What is $RVO
    • Earning Methods
    • Tokenomics
    • DAO Governance
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  • Wearing to Earn:
  • Maximize Data Generation:
  • Data Monetization:
  1. Token Introduction

Earning Methods

Wearing to Earn:

You earn $RVO just by wearing the Rayvo and going about your day. The glasses, through the Data Refracter Lens, collect anonymized data in the background, and you are rewarded with tokens for contributing this data.

  • Mechanism: Users earn $RVO tokens simply by wearing Rayvo smart glasses that are equipped with the Data Refracter Lens.

  • Data Refracter Lens: The Data Refracter Lens is key, it activates the "wear-to-earn" functionality.

  • Data Contribution: By wearing the glasses, users passively contribute real-world data to the decentralized ecosystem. The examples of data mentioned are:

    • Location: Where the user is going, their movements, and points of interest.

    • Pictures and Videos Capture: What the user would like to watch, and views of interest.

    • Voice Interactions: Voice commands given to the glasses, or potentially even conversations.

    • Etc.

  • Consistency Rewards: The more consistently users wear their glasses, the more $RVO tokens they earn. This encourages continuous and regular use of the Rayvo.

Maximize Data Generation:

You can choose to purchase the Rayvo rings, which can collect the user's health data and generate more data for your own user's profile. And this additional data will increase the token reward.

  • Mechanism: Connect Rayvo ring with Rayvo Companion App under your Rayvo glass account.

  • Data Contribution: By wearing the rings, users passively contribute real-world data to the decentralized ecosystem. The examples of data mentioned are:

    • Heart Rate: Real-time monitoring of heart rate, which can reflect exercise intensity, stress level or cardiovascular health.

    • Skin Temperature: Monitors changes in skin temperature, which may be used to detect fever, physiological cycle or body recovery status.

    • Resting Heart Rate (RHR): Records the lowest heart rate when resting, which is used to monitor cardiovascular health trends in the long term.

    • Sleep Duration: Records total sleep time

    • Steps: Records walking steps through the accelerometer.

    • Exercise Type and Duration: Some smart rings can identify activities such as running and walking, and record the duration.

    • Etc.

  • Consistency Rewards: The more users wear the ring while wearing their glasses, the more additional $RVO tokens they earn.

Data Monetization:

You can choose to earn even more $RVO by allowing your anonymized data to be used by researchers, AI companies, or advertisers. You remain in control of your privacy, as the data is anonymized, and you are compensated for the value of your data.

  • Mechanism: Users can monetize their anonymized data. This is an additional revenue stream, on top of the "Wear-to-Earn" rewards.

  • Anonymization is Key: Crucially, the data is anonymized before being made available for monetization. This is vital for user privacy and aligns with the privacy-focused ethos of Rayvo.

  • Data Stakeholders: Anonymized data can be made available to various stakeholders who find it valuable:

    • Research Institutions: For scientific research, urban planning, social studies,(e.g., aggregated location data for mobility studies).

    • AI Training Platforms: To improve and train AI models (e.g., voice interaction data to train voice assistants, or aggregated location data for location-based AI).

    • Advertisers: For targeted advertising (e.g., anonymized location and demographic data to understand user behavior and ad targeting).

    • Etc.

  • Revenue Stream: Monetizing data creates an additional revenue stream for users.

  • Privacy and Security Assurance: Data monetization is presented as being done while ensuring data privacy and security. This reiterates the project's commitment to protecting user data even when it's being utilized for monetization.

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