Project background
As Enersponse expanded its demand response ecosystem and utility integrations, the company faced increasing complexity in managing distributed energy events, OpenADR communication, and cloud infrastructure scalability.
The existing Demand Response Management System (DRMS) already supported real-time utility communication and distributed Virtual End Nodes (VENs), but the growing number of connected energy assets exposed architectural limitations in scalability, monitoring, deployment workflows, and event orchestration.
To support future growth and utility-grade reliability requirements, Enersponse partnered with Vakoms to modernize and optimize the platform’s cloud-native infrastructure, improve OpenADR interoperability, and strengthen distributed event processing capabilities.
What was the customer's request?
- Prana requested full-cycle R&D and development support to build Prana Platinum — a next-generation smart decentralized ventilation system. The scope covered hardware architecture validation, embedded firmware, multi-protocol connectivity, air quality sensor integration, a mobile app, and a cloud platform — all from scratch.
What did the client already have?
- The client had an existing product line of decentralized ventilation units and a functioning cloud platform on ThingsBoard. Prana Platinum required a complete rethink of the electronics, firmware, and user experience — leveraging the existing cloud infrastructure as a foundation.
Solution we delivered
Where did we start?
Our team began with a full architecture review and R&D phase — evaluating seven SoC families, defining power isolation requirements, and establishing the sensor measurement architecture across four airflow points. From this foundation we designed and implemented the embedded firmware, connectivity stack, mobile app, and cloud integrations in parallel phases — delivering a production-ready platform while iterating with the client on prototype hardware.

Our Development Process
R&D & Hardware Architecture
Evaluated multiple industry-leading MCUs against I/O requirements, connectivity standards, supply chain risks, and ecosystem maturity. Selected an optimal system-on-chip offering native Wi-Fi 6, BLE, and certified Matter/Thread support. Designed a split power architecture with isolated MCU and motor rails to ensure maximum system stability and efficiency.
Embedded Firmware Development
Built FreeRTOS/ESP-IDF firmware with task-based decomposition across motor control, sensor polling, display, connectivity, and diagnostics. Implemented dual-motor PWM control with tachometer feedback and current sensing, step-counted damper synchronization, and eleven operating modes via explicit state machine logic — including Auto Air Quality, Auto Temperature, Winter, Bypass, Intelligent, and Standby modes.
UX/UI & Operational Experience
Designed a unified visual system across the on-device display, iOS and Android mobile app, and web interface. The display supports 170° viewing angle and daytime readability, showing operating mode, fan speeds, date/time, sensor readings, and scenario status. Mobile app includes scenario builder, weekly scheduling, AQI dashboard, device sharing, and group management.
Connectivity & Smart Home Integration
Implemented simultaneous control across four channels: mobile app (Wi-Fi/BLE), IR remote, Matter smart home platforms, and physical controls. Matter on ESP32-C6 enables native Apple HomeKit, Google Home, and Amazon Alexa integration without bridges. Thread 1.3 mesh supports multi-unit grouping with synchronized scenarios across devices in the same building.
IoT & Cloud Development
Extended Prana's existing ThingsBoard platform with historical sensor log storage (temperature, humidity, CO2, VOC, PM1.0/PM2.5, AQI), remote scenario management, service technician error dashboards, and user consent-based data collection. SNTP time sync with on-board RTC fallback ensures scenario accuracy regardless of connectivity.
Maintenance & Ongoing Development
Continuing to support the platform through hardware revision cycles, firmware updates, sensor driver additions, and smart home compatibility updates as the Matter ecosystem evolves. Expanding filter identification logic and diagnostic capabilities as new hardware variants are introduced.
The Team Involved In The Project
Embedded Engineers
2
Hardware Engineer
1
Mobile developer
1
Cloud Engineer
1
UX/UI Designer
1
QA Engineer
1
Project Manager
1
Project Challenges And Our Suggestions
Selecting the right SoC for Matter and multi-protocol connectivity support
Evaluated seven MCU families based on connectivity capabilities, I/O availability, Matter certification readiness, and supply chain stability. Selected ESP32-C6 for its native support of Wi-Fi 6, BLE 5.3, Matter, Thread, and Zigbee, eliminating the need for additional co-processors.
Motor switching noise impacting sensor accuracy
Designed a split power architecture using dedicated Mean Well AC/DC power supplies for motors and isolated power rails for the MCU and sensors. Implemented per-channel current sensing to enable diagnostics and power monitoring.
Managing 11 operating modes with potential conflict scenarios
Developed a state-machine architecture with clearly defined transition rules. Added scheduling conflict detection and user-facing notifications in the mobile application to prevent overlapping operating scenarios.
Identifying filter types without barcodes or manual configuration
Implemented a physical micro-switch matrix within the filter shaft. Firmware detects the switch pattern during startup, automatically identifies the filter type, loads the correct control algorithm, and initializes filter lifetime tracking.
Synchronizing damper operation with fan ramp-up sequences
Created a control sequence where the damper opens before the fan reaches operating speed. Step-based position tracking prevents pressure spikes and reduces mechanical stress during startup.
Enabling self-diagnostics without additional hardware sensors
Developed diagnostic algorithms using static pressure measurements when motors are inactive. Combined tachometer feedback with current anomaly analysis to detect motor stalls without dedicated diagnostic sensors.

Impact
By engineering Prana Platinum from hardware architecture through cloud platform, Indeema delivered a validated, production-ready smart ventilation system that positions Prana to compete in the premium connected HVAC market across Europe with native smart home compatibility, closed-loop air quality automation, and a scalable multi-unit architecture.
Before And After Cooperation With Indeema
Before:
Product concept without validated hardware architecture
No MCU selected or benchmarked across supply chain
Sensor requirements and measurement points undefined
No embedded firmware or power architecture
Smart home integration unplanned
No mobile app or unified UX system
After:
Validated hardware architecture with full component spec
ESP32-C6 selected — Wi-Fi 6, BLE 5.3, Matter-certified
10+ sensors across 4 airflow measurement points
Dual-motor FreeRTOS firmware with 11 operating modes
Native Matter/Thread/Zigbee smart home support
iOS + Android app with ThingsBoard cloud platform
Technical Highlights
Microcontroller & Connectivity
ESP32-C6
Wi-Fi 6 (802.11ax)
Bluetooth 5.3
Thread 1.3
Zigbee 3.0
IR Remote




