aminobots lens — poweriq · codename poweriq
cut industrial energy bills with edge ai.
Edge IoT controllers + cloud AI for industrial energy. Raspberry Pi 4 + L&T HT meter via Modbus RS485. WBSEDCL ToD compliance + MD-floor automation + PF rebate captured in software.
01 · capabilities
what's inside
- Edge controllerRaspberry Pi 4 polls L&T or Schneider HT meters via Modbus RS485 at 5-minute granularity.
- 50+ parameters trackedVoltage, current, power factor, frequency, kWh, kVAh, harmonics. All audit-logged.
- ToD tariff engineWBSEDCL Time-of-Day tariff schedule encoded as executable rules. PF rebate thresholds. MD floor band.
- Load forecasting MLHourly forecast with confidence bands. Anomaly detection on consumption patterns.
- MD-floor automationAutomated load shedding / shifting commands enforce MD floor and capture PF rebate.
- Edge resilienceEdge buffer survives cloud disconnects. IoT controllers keep running offline; sync resumes on reconnect.
- ESG Scope-2 reportingAudit-ready Scope-2 emissions reduction report with full methodology.
02 · architecture
meters at the edge. dashboards in the cloud.
Raspberry Pi reads HT meter via Modbus. Greengrass pre-processes at the edge. MQTT broker forwards to cloud. Time-series store captures 5-minute granularity. Tariff engine + forecast ML decide load actions. Commands flow back to edge controllers. ESG reports export audit-ready.
l&t meter ← modbus ← raspberry pi 4 (edge)
↓ mqtt
iot core · time-series db · forecast ml
↓
tod policy → md-floor automation
↓
command queue → edge → switch panel
↓ mqtt
iot core · time-series db · forecast ml
↓
tod policy → md-floor automation
↓
command queue → edge → switch panel
03 · lighthouse
live in production
ready to evaluate
start with a diagnose.
Two to three weeks. Five to ten lakh. A written scorecard with topology recommendation, cost ranges, and remediation plan. No commitment to build.
request diagnose
DPDP-ready by design
AWS · Azure · GCP
blueprint · patent pending
India residency · on-prem option