Praesense

Praesense is an open-source framework for privacy-preserving sensing and edge analytics. It enables organizations to collect sensor data from distributed devices, perform local processing, and share only aggregated insights with downstream systems. The design emphasizes data minimization, strong access controls, and interoperability with common industrial protocols.

The project originated as a collaboration among researchers at Northside University and several technology companies in 2019. The initial release in 2020 introduced a modular microservice architecture and a privacy-focused data pipeline. Subsequent updates in 2022 and 2024 added extended sensor adapters, improved security features, and cloud orchestration capabilities, expanding its applicability across industries.

Praesense uses a three-layer architecture: an edge layer for data collection and preprocessing; a secure aggregation layer that employs differential privacy and secret sharing to compute global metrics without exposing individual readings; and a cloud layer for governance, model deployment, and analytics management. It supports trusted execution environments for confidential computing, federated learning, and standard protocols such as MQTT, CoAP, and REST APIs. The framework is designed to integrate with existing SCADA and IIoT stacks.

Applications include urban air quality networks, traffic monitoring, energy usage optimization, and industrial equipment health monitoring. Researchers use Praesense to run anomaly detection and predictive analytics while keeping sensitive data on local premises.

Praesense has been adopted in several pilot programs and is noted for improving data privacy and regulatory compliance. Critics point to added computational overhead and the need for specialized expertise to implement and tune privacy controls.