Architecture
Architecture & Technical Flow
Presens Network is designed as a modular, software-first DePIN architecture that transforms time–location signals into structured spatiotemporal intelligence.
4-Layered Architecture
Pulse Node Layer
Decentralized endpoints (apps and extensions) that generate anonymous time–location signals at the edge of the network
Signal Layer
Preprocesses raw signals with anonymization and hashing before aggregation into spatiotemporal batches
Validation Layer
Detects anomalies, filters spoofed or inconsistent data, and applies weighting for signal quality
Data Access Layer
Exposes spatiotemporal intelligence through APIs and query endpoints for enterprises, developers, and AI/robotics teams
Technical Flow
Signal Capture
Pulse Nodes emit timestamped location signals
Anonymization & Hashing
Personally identifiable information is stripped, and signals are cryptographically hashed
Aggregation
Signals are clustered into spatiotemporal batches for efficiency
Validation
Anti-spoofing checks, statistical anomaly detection, and device-level verification strengthen integrity
Query & Access
Aggregated datasets are served via decentralized APIs for use in AI model training, robotics navigation, and smart city analytics
Settlement
Validated contributions are recorded for reward distribution
Optional Premium Extension
While Presens operates on a streamlined four-layer architecture, certain enterprises and regulated industries require additional assurances of transparency and compliance. To meet these needs, Presens offers an Anchoring Extension, a premium service that anchors aggregated signal batches on-chain.
Verifiable audit trails – Clients can cryptographically verify the integrity of datasets.
Tamper-resistance – Anchored proofs prevent retroactive alteration of data.
Compliance-ready – Designed for industries where regulatory frameworks demand immutable evidence.
Presens ensures that the network remains efficient, privacy-first, and scalable by default, while still providing paid, optional transparency features for clients who demand them.
Design Principles
Privacy-first
Anonymous by default; no audio, video, or IDs ever processed
Efficiency
Aggregation reduces on-chain load, ensuring scalable throughput
Interoperability
APIs and data formats are designed to plug into existing AI, robotics, and enterprise workflows
Resilience
Decentralized architecture prevents single points of failure and strengthens trust
Summary
Pulse Node Layer
Signal generation
Core (free) and Prime (paid) Nodes passively contribute time–location signals.
Signal Layer
Capture & preprocess
Data is anonymized, hashed locally, then batched by hex-tile and time window.
Validation Layer
Quality & integrity checks
Anti-spoofing, anomaly detection, and quality weighting applied.
Anchoring Layer (Optional)
Transparency & immutability
Aggregated batches committed on-chain (Merkle root anchoring).
Data Access Layer
Query & integration
Spatiotemporal layers indexed off-chain, accessible via APIs and SDKs.
Settlement Layer
Contributor incentives
Nodes scored, token emissions distributed, Prime multipliers applied.
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