Map2Earn to help integrate the physical and virtual worlds

Blockchain fuels the development of new and often unpredictable markets and economies driven by the demand for innovation. From unprecedented crowdfunding mechanisms to Play-to-Profit (P2E) and Movement-to-Money (M2E) models, decentralized technology is empowering communities like never before.

One of the next big things in today’s tech revolution is something called Map2Earn – an emerging and rapidly growing trend that revolves around an economic model that incentivizes people to scan locations and physical buildings to draw 3D maps. While this isn’t a standalone market yet, Map2Earn may play an integral role in Augmented Reality and the Metaverse. Both are a multi-billion dollar market that is expected to expand rapidly in the coming years.

Some analysts expect the Metaverse market to cross the $1 trillion mark by 2030. The augmented reality and virtual reality market could grow to around $500 billion by then.

Many AR and Metaverse use cases involve map simulation. The ecosystem will soon require Google Maps-like alternatives. The Map2Earn model will accelerate the creation of high-quality 3D maps with the help of communities, while incentivizing participants for their efforts. While the requirements vary from case to case, most of the time, users are invited to take pictures of physical locations with their smartphones.

What’s different about Map2Earn

Map2Earn has some great benefits that anyone with a smartphone can take advantage of. Unlike other similar fashion economy models, such as P2E and Move-to-Ear, which require more effort, Map2Earn can reward users for simply taking a few snapshots while walking, going to office, or traveling for fun.

Thanks to Map2Earn, blockchain and Metaverse projects with large communities can create detailed 3D maps of the physical world and offer unique AR and Metaverse experiences. Currently, one of the problems with most virtual world projects is that GPS accuracy is limited when locating an AR asset geographically, being within six meters at best. In addition, it is almost impossible to place AR assets inside. An ultra-detailed map created with the Map2Earn feature can increase localization accuracy to just 20 cm. This could enable creators to more accurately superimpose AR assets on existing buildings, walls, or statues, generating experiences that were not possible before.

Since Map2Earn is a relatively new concept and still not very popular, it comes with great revenue generation opportunities for users who can contribute at an early stage of map creation.

All users need to do is find real Metaverse and AR projects to create detailed maps by implementing the Map2Earn model. One of the best examples today is OVER, a decentralized blockchain-powered infrastructure for the AR Metaverse. The platform merges the physical and virtual worlds to provide unique augmented reality experiences, opening the door to multiple use cases.

The Metaverse is fueled by its native token with the OVR indicator. Owners can use the token to purchase OVRLand, a 300 square meter hexagonal plot mapped one-on-one to a real geographic location and represented by a non-fungible token.

The goal of OVER is to build the most comprehensive and detailed Web3-based 3D map of relevant locations around the world, at home and abroad. Map2Earn plays a major role in this ongoing process. In fact, OVER is the project that greatly contributed to defining and enhancing the Map2Earn model.

Anyone with a smartphone can spend about five minutes photographing any OVRL piece to contribute to the creation of the map. By default, each time a user maps a location, they will own the data generated through the NFT (OVRMap), like a crowdsourced version of Google Maps owned by its contributors. Users are also rewarded with OVR tokens for their efforts through contests and sponsored mapping initiatives. Any OVER user can become a mapper in this way. During the process, users create three main items that the NFT represents:

  • 3D Point gives creators a visual representation of the 3D structure of the site they want to augment.
  • AI Neural Render – This feature can be used to create a digital twin of the particular location.
  • Determine the exact geographical location of the augmented reality assets at home and abroad.

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Map2Earn’s future

OVER launched the Map2Earn Beta program in December 2022, which can be considered the most important experiment of this model. It is still an emerging concept and is expected to be implemented by other AR and Metaverse projects looking to empower their communities while enhancing geolocation accuracy.

The accuracy of the new translation feature will enable creators to relate specific digital experiences to physical objects, including buildings, walls, and statues. For example, one can bring a statue to life thanks to 3D animation or deploy unique experiences on each floor of a multi-storey building as part of an AR journey.

Map2Earn is a powerful model poised to help merge the physical and virtual worlds at an accelerated pace.

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