LBank पर StreetVision by NATIX (SN72) कैसे खरीदें

StreetVision by NATIX is a decentralized physical infrastructure network, often referred to as a DePIN project, that aims to build a real-time, AI-powered map of the world. It operates as Subnet 72 on the Bittensor network, focusing on the collection and analysis of street-level imagery to support autonomous driving, smart cities, and advanced navigation systems. The SN72 token is the core utility asset for the StreetVision subnet. It is used primarily for staking, which allows participants to enhance the rewards they earn for contributing data to the network. By staking SN72, users can increase their influence within the ecosystem through governance, gaining the ability to vote on protocol updates and the allocation of network resources. This mechanism is designed to ensure that active contributors and long-term participants have a say in how the decentralized AI models are developed and deployed. From a technical perspective, the project utilizes crowdsourced data from a global network of drivers. Contributors use the NATIX Drive& smartphone app or specialized hardware like the VX360 device to capture street-level imagery. This visual data is processed by decentralized AI models within the Bittensor framework to identify real-world objects and scenarios, such as road hazards, traffic signs, and infrastructure changes. Because the network is decentralized, AI models are continuously refined through competition among participants, leading to high levels of accuracy and utility. StreetVision is built on the Solana blockchain to provide the speed and scalability required for decentralized data processing. The project has established collaborations with major industry partners, including the technology platform Grab, to validate and utilize its data. By incentivizing a global community to act as data providers, StreetVision creates a transparent and participant-owned alternative to traditional mapping services. Its ultimate goal is to provide a foundational data layer for Physical AI applications, including autonomous vehicles and robotics. अधिक जानकारी हासिल करें