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Iot Engineer
Use when designing IoT systems with MQTT messaging, edge computing, device management, and telemetry pipelines
About this skill
Use when designing IoT systems with MQTT messaging, edge computing, device management, and telemetry pipelines
SKILL.md
iot-engineer.SKILL.mdPlace it in your Syntic skills folder. For Syntic Code, install in your local skills directory, review the contents and run it in a controlled environment first.
---
name: Iot Engineer
description: Use when designing IoT systems with MQTT messaging, edge computing, device management, and telemetry pipelines
category: Specialized
version: 1.0.0
tools: []
---
# IoT Systems Architecture
Design connected device systems from edge sensor through cloud backend. Work with MQTT, CoAP, and AMQP messaging protocols, edge computing frameworks, device provisioning, and time-series storage. Design for intermittent connectivity, constrained bandwidth, and autonomous offline operation.
## System Development
1. Design device data model including sensor readings, metadata, configuration parameters, firmware version, with schema versioning for field evolution.
2. Select messaging protocol based on device constraints: MQTT for reliable bidirectional communication with QoS levels, CoAP for extremely constrained devices, AMQP for enterprise integration.
3. Design MQTT topic hierarchy with structured namespace (devices/{device-id}/telemetry, devices/{device-id}/commands, devices/{device-id}/status) enabling fine-grained subscription filtering.
4. Implement device provisioning flow including identity creation, certificate enrollment, fleet grouping, configuration push, supporting zero-touch onboarding at scale.
5. Build edge processing pipeline performing local aggregation, filtering, anomaly detection to reduce bandwidth and enable offline operation.
6. Design telemetry ingestion pipeline with time-series storage (InfluxDB, TimescaleDB, QuestDB) optimized for high-frequency writes and downsampled retention policies.
7. Implement over-the-air (OTA) firmware updates with staged rollouts, automatic rollback on health check failure, bandwidth-efficient delta updates.
8. Build device shadow or digital twin maintaining last known state and desired state, reconciling upon reconnection after offline periods.
9. Implement alerting rules on telemetry streams with configurable thresholds, dead-band hysteresis preventing alert storms, escalation policies for unacknowledged alerts.
10. Design security layer with mutual TLS for device authentication, encrypted payload transmission, certificate rotation, revocation for compromised devices.
## Technical Standards
- Devices buffer telemetry locally during connectivity loss, transmitting in order upon reconnection with server-side deduplication.
- MQTT QoS levels chosen per topic: QoS 0 for high-frequency telemetry, QoS 1 for commands, QoS 2 for provisioning and configuration changes.
- Time-series data stored with nanosecond precision timestamps in UTC with device clock drift detection and correction.
- Device certificates have maximum 1 year lifetime with automated renewal starting 30 days before expiration.
- Edge processing operates within target hardware memory and CPU constraints, profiled under sustained load.
- OTA updates validate firmware signatures before applying and confirm successful boot before committing.
- Device telemetry uses compact binary formats (CBOR, Protobuf) minimizing bandwidth on constrained networks.
Install
Syntic App
- 1Create a dedicated folder for this skill in your local skills library.
- 2Place SKILL.md into that folder.
- 3Restart Syntic and invoke this skill on matching tasks.
Syntic Code (CLI)
- 1Save SKILL.md in your local Syntic Code skills directory.
- 2Keep related files in the same skill folder.
- 3Run in a safe environment and validate outputs.