Battery-Free Ambient Room & Occupancy Sensor
US-based smart-building / IoT startupA battery-free environmental sensor detects room conditions and occupancy while minimizing energy consumption and maintenance requirements.
Where AI accelerated vs. where our engineers led.
Every project follows the same Rivix Split — AI drafts the mechanical work, a named engineer reviews and owns every decision that touches safety, cost, or a regulatory limit.
Where AI accelerated
- Sensor drivers & firmware
- Communication implementation
- Data-processing algorithms
- Backend services
- Test generation & documentation
Where our engineers led
- Energy budget & harvesting architecture
- Hardware selection & sensor placement
- RF architecture
- Ultra-low-power design
- Reliability
Technical deep-dive
Additional detail on architecture, stack and implementation specifics for this engagement.
Architecture & stack
The sensor harvests ambient energy (light and/or thermal/kinetic sources, depending on deployment) to power an ultra-low-power MCU and wireless radio, eliminating the battery entirely. Firmware is built around an event-driven, mostly-sleeping execution model that only wakes for sensing and transmission windows.
- Ambient energy harvesting (light/thermal/kinetic, deployment-dependent) powering an ultra-low-power MCU + radio
- Event-driven firmware, mostly asleep, waking only for sensing/transmission windows
- Low-power wireless link to a gateway, gateway-to-cloud for aggregation
Connectivity & data pipeline
Given the intermittent, harvested power budget, the device transmits compact occupancy/environmental readings on a duty-cycled schedule over a low-power wireless protocol to a gateway, which forwards data to the cloud for aggregation and building-management-system integration.
- Duty-cycled transmission scheduled around available harvested energy, not wall-clock time
- Compact payloads to minimize radio-on time per transmission
- Gateway-side aggregation before data reaches the cloud/BMS integration layer
Key engineering challenges
Designing firmware that can operate correctly under an unpredictable and sometimes-interrupted power supply — including brownout handling and state persistence across power gaps — was the central engineering problem, on top of the usual ultra-low-power sensing and RF design work.
- Firmware correctness under unpredictable, sometimes-interrupted power availability
- Brownout handling and state persistence across power gaps
- Ultra-low-power RF and sensing design within a harvested (not stored) energy budget
Why this approach
Energy harvesting was the client's core value proposition (zero-maintenance sensors), so the firmware and hardware architecture had to be designed around power availability as a first-class constraint from day one, rather than treating power as an optimization applied afterward.
- Firmware architecture treats power availability as a first-class input, not an afterthought
- Event-driven (vs. polling) execution chosen to match an intermittent power supply
- Gateway-mediated uplink chosen over direct cloud connection to reduce per-device radio cost