ArticleSensors (Basel, Switzerland)2026
Characterization of Latency Sources in a MicroPython-Based ESP32 Edge-Cloud Sensor Network.
Article in Sensors (Basel, Switzerland), 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
This paper presents the design and experimental characterization of a distributed ESP32/MicroPython edge-cloud sensing system with packet-level latency decomposition. Sensor nodes transmit periodic telemetry to an ESP32 gateway over ESP-NOW; the gateway appends reception and MQTT-publication timestamps and forwards records through a local Mosquitto bridge v2.1.2, EMQX Cloud v5, Telegraf v1.36.0, and InfluxDB Cloud Serverless (Storage Engine Version 3). A three-probe two-way gateway-referenced synchronization procedure provides corrected sender timestamps while exposing an interval-based synchronization-uncertainty diagnostic. The bridge-assisted campaign comprised three independent 30 min repetitions with one, three, and five active nodes. Across runs, mean gateway-referenced node-to-gateway latency was 23.17 ± 0.13 ms, 24.13 ± 0.12 ms, and 24.84 ± 0.47 ms, respectively; the corresponding p95 values were 28 ms, 33 ms, and 37-38 ms. Mean gateway-processing latency remained nearly unchanged at 13.31-13.46 ms. Exact full-run database-visible PDR was 100% in all one-node runs, 99.28-99.88% in the three-node runs, and 96.75-97.05% in the five-node runs. Independent GPIO/oscilloscope validation showed a reproducible positive software-to-hardware difference of 12.132 ± 1.819 ms across run means, so the local metric is interpreted as a gateway-referenced application-level delivery metric rather than unbiased physical one-way radio latency. Relative to aggregate end-to-end reporting, the instrumentation separates local, gateway, and downstream ingestion contributions rather than claiming a universally faster transport method. Quantitative performance and scaling claims are confined to the evaluated bridge-assisted configuration and controlled indoor periodic workload.
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