Jeffrey Peterson¹
¹Technology Entrepreneur. pub. 03/11/2025
The rise of autonomous systems, augmented reality, and artificial intelligence has exposed a critical gap in our digital infrastructure. While these technologies excel at processing abstract data, they lack a standardized way to understand physical spaces as humans do - with rich context, history, and social meaning. Current solutions are fragmented across proprietary systems and even when they are capable of dynamic updates, they are slow to update, leading to incomplete comprehension of three dimensional spaces, duplicated efforts and artificial barriers between applications.
The mobilexyz protocol addresses this challenge by providing a decentralized network layer for rapid, prioritized dynamic multidimensional spatial data exchange allowing Humans, Artificial Intelligence, and Robotics to work together to reimagine and better understand the world around us. At its core are "datastructs" - compact, self-contained data packages that combine precise spatial coordinates with layers of contextual meaning. This enables machines to develop human-like spatial awareness while maintaining the precision needed for navigation and interaction.
This paper presents the technical architecture of mobilexyz, its implementation considerations, and the economic model that enables sustainable network operation. We examine how the protocol enables new capabilities in autonomous navigation, augmented reality persistence, and smart city infrastructure while ensuring open access and collaborative development.
An autonomous delivery robot approaches a building entrance. Beyond its coordinates, the robot needs to understand multiple layers of spatial context: Is this the correct entrance? What are the access hours? Are there temporary construction barriers? Is this a restricted area? Current systems handle these questions through custom, application-specific solutions. Each autonomous system, AR platform, and implementation builds its own spatial understanding from scratch.
Moreover, in today's rapidly evolving urban and commercial environments, spatial data that is accurate one week may become outdated the next. Construction projects, temporary events, seasonal changes, and emergency situations can all dramatically alter the accessibility and context of physical spaces. Current systems, built on static, "flat" data structures, lack the fundamental capability to capture and propagate these dynamic changes in real-time. This limitation becomes particularly critical when the changes affect multiple stakeholders - humans navigating physical spaces, AI systems making routing decisions, and robots executing tasks - each requiring timely updates to their spatial understanding.
This fragmentation creates significant inefficiencies. Spatial data is collected redundantly, stored in incompatible formats, and locked within proprietary systems. More importantly, it prevents machines from developing the rich spatial understanding that humans take for granted. We naturally grasp that spaces have multiple layers of meaning - physical characteristics, historical significance, social context, emergency protocols, and planned changes. Enabling machines to understand space with similar sophistication requires a fundamental protocol innovation.
The mobilexyz protocol implements spatial awareness through a carefully designed data structure that mirrors human spatial understanding. Rather than treating locations as simple coordinates, the protocol enables rich contextual relationships while maintaining the precision needed for machine navigation.
At the foundation of mobilexyz are datastructs - self-contained packages limited to 8KB that combine spatial coordinates with contextual metadata. Each datastruct is uniquely identified by a SHA-256 hash of its contents, enabling content-addressed storage across decentralized networks. This approach allows datastructs to be cached, replicated, and verified without central coordination.
A datastruct begins with essential routing information: timestamp, priority level, and type identifiers. The priority system enables efficient network handling - critical updates about emergency routes or safety hazards can propagate rapidly, while historical information flows at normal priority. This mirrors how humans naturally prioritize spatial information.
The protocol's true innovation lies in its spatial reference structure. Each datastruct can link to up to 64 locations using precise 3D coordinates. Beyond simple points in space, these references carry multiple layers of meaning through a sophisticated tagging system. A single location might simultaneously represent a physical entrance, a historical landmark, and a navigation waypoint, each aspect carrying its own precision level and temporal context.
This layered approach solves a key challenge in machine spatial awareness. A human understands that a building entrance means different things to different users at different times - delivery access might be restricted to certain hours, while emergency services require 24-hour access. The protocol's tagging system captures these nuances through standardized prefixes: "physical:" for tangible characteristics, "historical:" for temporal context, "social:" for usage patterns, and "emergency:" for critical access information.
The protocol operates through a network of relay servers, each serving specific geographic regions. This geographic awareness enables efficient routing - spatial information naturally flows to the relays and clients most likely to need it. New relays announce their coverage areas through special datastructs, enabling organic network growth based on demand.
Data flows through the network via websocket connections using a simple message format:
["type", "subject", payload]
This straightforward approach enables easy debugging while maintaining efficient transmission. The protocol includes basic message types for publishing datastructs, requesting spatial data, and managing subscriptions. Each relay maintains a spatial index using a configurable grid system, enabling rapid geographic queries.
The mobilexyz protocol builds upon proven cryptographic standards while introducing novel mechanisms for spatial data verification. Like NOSTR, it uses secp256k1 public key cryptography for creator identification and Schnorr signatures for verification. This choice enables direct compatibility with existing web3 infrastructure while providing the security properties needed for trusted spatial data.
A key innovation is the protocol's handling of collaborative spatial information. Each datastruct supports up to 255 verified contributors, enabling natural collaboration while maintaining clear provenance. An architect might define a building's physical structure, while facility managers add access protocols, and historians contribute temporal context. Each contribution is cryptographically signed, creating an immutable record of how spatial understanding evolves.
The trust system operates through a sophisticated but practical mechanism. Each creator carries a trust level byte, where 0xFF indicates maximum reliability. Rather than implementing rigid restrictions, these trust levels inform how systems weight and prioritize spatial information. This mirrors human spatial learning, where we naturally assign different levels of confidence to different sources of information about a space.
Datastructs propagate through the network based on both priority and geographic relevance. When a client publishes a new datastruct, connected relays examine its spatial references. Relays serving the referenced geographic regions store the datastruct and forward it to peer relays with overlapping coverage. This geographic routing happens automatically, ensuring spatial information reaches the systems most likely to need it.
The protocol implements a hybrid persistence model that balances efficiency with data availability. Relays maintain rolling windows of recent datastructs, typically 30-90 days, while critical spatial information can be flagged as "spatial anchors" for permanent storage. This designation requires validation from multiple trusted creators, ensuring that permanently stored spatial data meets community standards.
Query systems support several access patterns:
Each query type is optimized for its intended use case while maintaining consistent response formats.
The operation of a global spatial awareness network presents concrete challenges that require careful economic design. Relay operators must maintain sophisticated spatial indices, store significant amounts of data, and provide reliable API access at scale. Content creators need incentives to contribute accurate spatial information and maintain its currency. These requirements demand a sustainable economic model that aligns network participant interests.
The mobilexyz protocol addresses these challenges through the mxyz token, implemented on Solana for its high throughput and low transaction costs. Unlike many web3 projects where tokens feel bolted on, mxyz serves essential protocol functions that would be difficult to implement through traditional payment models.
Content creators participate in this economic model. High-quality spatial data, validated through actual usage and peer verification, generates token rewards for its creators. This creates a sustainable incentive for maintaining accurate spatial information while enabling contributors to capture value from their expertise.
The protocol implements three API access tiers:
This tiered structure ensures the network remains accessible for development while providing sustainable economics for production usage. Token staking, rather than consumption, enables predictable costs for API consumers while maintaining economic security.
Consider an autonomous delivery service operating across multiple cities. Through mxyz tokens, the service gains reliable access to spatial data needed for navigation. Their API usage generates rewards for relay operators providing infrastructure and content creators maintaining spatial accuracy. This creates a highly productive economic creation cycle where economic incentives align with network utility.
This section provides comprehensive implementation requirements for the mobilexyz protocol. These specifications ensure interoperability while enabling innovation in specific implementations.
A datastruct consists of ordered fields serialized without delimiters. The complete byte string is hashed using SHA-256 to generate its unique identifier. All multi-byte integers use big-endian encoding, and all text must be UTF-8.
Relay connections use websocket transport with JSON messages:
["type", "subject", payload]
Geographic indexing uses a configurable grid system:
New relays join the network by publishing a special datastruct containing:
This section addresses practical considerations for implementing mobilexyz nodes, relays, and client applications. While the protocol specifications define what must be implemented, these guidelines explain how to implement it effectively.
A production relay must carefully balance resource usage with service quality. The geographic indexing system forms the core of relay performance. We recommend implementing a multi-level spatial index:
Primary Index: R-tree structure for rapid spatial queries
Secondary Indices:
Production relays should implement a tiered storage system:
Data retention policies should consider both time and importance:
Network optimization requires careful handling of concurrent connections:
Clients should implement sophisticated caching strategies:
Error handling requires particular attention:
The protocol's use of IEEE 754 double-precision floating point numbers requires careful implementation:
The mobilexyz protocol represents a fundamental advancement in how humans, artificial intelligence and machines can work together to better understand three dimensional spaces. Moreover, it will allow the re-conceptualization of many of the best data-centric consumer services and applications from "web1" and "web2", for "web3" and beyond. By combining precise multidimensional spatial coordinates with rich contextual awareness and trust metrics, it enables something that has not yet existed - for each of humans, artificial intelligence and robotics to either enhance or develop human-like spatial understanding while enabling accuracy needed for cognition, navigation, interaction, and much richer data processing in a rapidly evolving digital world that has, thus far, consisted primarily of "flat" data.
The protocol's careful balance of technical sophistication and practical implementation creates a foundation for the next generation of autonomous systems, augmented reality, and smart city infrastructure. Through its economic model, mobilexyz ensures sustainable network operation while rewarding both infrastructure providers and spatial data contributors.
As autonomous systems become increasingly prevalent in our daily lives, the need for standardized spatial awareness becomes critical. The mobilexyz protocol fills this gap not through marketing promises, but through careful technical design and practical utility. Its implementation will enable new categories of applications while solving real challenges in machine spatial awareness.
The future of human-machine interaction requires next generation data paradigms that conceptualize three dimensions as we do - not just as coordinates, but as places with history, meaning, and rich, dynamic multidimensional context. Mobilexyz provides the protocol foundation for this future.