This document describes a starter kit called "SmartEnergy" that provides an end-to-end industrial IoT solution using open source technologies. The stack includes mbedOS running on an STM32 microcontroller, ZigBee, MQTT, NodeJS, InfluxDB for time-series database, and Grafana for visualization. MbedOS is highlighted as a powerful RTOS for edge computing with over 13,000 git commits and strong community support. InfluxDB is noted for its high performance time-series data storage with nanosecond timestamps and built-in downsampling and retention policies.

1. Starter-Kit “SmartEnergy”
From an end-2-end solution to a reference Industrial
IoT pipeline
Lorenzo Maiorfi
Naples, November 24th 2017

3. Any Industrial IoT platform/reference-app should be…
● Reliable
● Reliable
● Reliable (yes, reliable)
● Based on (actual) standards
● Built on a (technology) stack entirely made of open-source layers
● Nice to have, but by far less important, fast, flexible, scalable, cool, etc

4. Our «stack»
● mbedOS (on STM32 microcontroller here, but plenty of targets are available)
● ZigBee
● MQTT (running on mosquitto broker here)
● NodeJS (with PM2 scheduler), running a custom ZigBee/MQTT «soft gateway»
● InfluxDB (time-series database)
● Grafana (web visualization front-end)
● (…many other adapters, exposing/consuming grpc/http/amqp/raw-tcp/wamp
endpoints…)

5. Focus on mbedOS 1/2
● Powered by ARM
● 13.090 git commits
● 351 active contributors, 1230 forks
● 450MB source repository
● ~100 targets (starting from €1 MCUs, such as STM32F1, based on Cortex-M3)
● Amazing community web site, with plenty of samples, libraries,
questions+answers

6. Focus on mbedOS 2/2
● Powerful RTOS
● Based on C++ from ground up
● Amazing tooling (multi-toolchain)
● Testing platform
● Astonishing base services (networking, cryptography, file-system, BLE, etc)
● Great for edge-computing also! (take a look at uTensorFlow sample)

7. Focus on InfluxDB
● Samples with nanosecond timestamp, with O(1) «insert» complexity
● Each sample is made of fields (numeric values) and tags (filtering, grouping)
● Builtin high-performance time-based math operators (down-sampling)
● Retention Policies (hi-res recent data to lo-res past data…step-by-step)
● Continuous Queries (built-in scheduler runs maintainance data manipulation
tasks)
● Available as-a-service (e.g. aiven.io)

8. Thanks !
Questions ?