Next step after using S-Soil MTEC-02B sensor in Milestone 2: Outdoor single sensor and saving telemetry data via Fledge software framework will be setting up an approach where developers can add new sensors or build a new software stack and provide private deployments to a subset of IoT devices in cloud infrastructure on on-premises.
The software build will be deployed with Open Horizon and uses open-source applications to be deployed to the RPi4 board.
Goals
- Prepare examples for contributors for SmartAg SIG by providing onboarding instructions and development environment.
- Build BSP distribution from scratch for developers to start adding new sensors or building a software stack in 15 minutes after cloning SmartAg-foundation repo.
- Create a custom example stack from scratch, flash the connected board remotely with Telegraf service docker app with plugin to read data from S-Soil MTEC-02B, save in InfluxDB and display the data in Grafana dashboard
- Update and deploy by node name Edge Node services running on IoT RPi4 board in LAN by using custom Edge Server docker image from developer host.
Containerised Architecture has been selected to build an isolated software components for Edge Node, Edge Server as well as for development and deployment tools.
It can be used without restriction, including without limitation to build isolated proprietary ecosystem for IIoT device management and secure device onboard.
In this milestone container images are based on open source components to display, debug and analyse data from Edge Node with connected S-Soil MTEC-02B sensor.
From the structure view of the IoT device there are static BSP image and dynamic services or stack which are added/updated after device was onboarded.
Edge Node BSP image should be configured, so the device could update itself after the boot and later when new services are available for it.
The stack consist of one or more preconfigured and tested software components which are running in isolated containers on the board and managed by Deployment Agent.
To provide more secure board management there are no IP ports exposed from the board outside in production (this is configured when initial BSP image for the board is created).
A single Edge Server may manage/update more than 100k of clusters or stand alone Edge Node IoT devices.
Each Edge Node may control a hundreds of wired or wireless and very limited IoT devices (Arduino, STM32, ESP32, etc.) or/and sensors.
Also with added AI services, Edge Node may act as distributed AI node with federated learning capabilities.
Here is how the software components are deployed on Edge Node and on Edge Server.
A software stack which is deployed to Edge Node, can be any set of proprietary or open-source containerised applications (Telegraf, Node-exporter, ) or more complex (EdgeX, Fledge) software frameworks
Distribution and Stack diagram
Prerequisites
Hardware
- Raspberry Pi4 model B 4GB+ RAM
- Industrial Soil Moisture & Temperature & EC Sensor MODBUS-RTU RS485 (S-Soil MTEC-02B)
- 16+ GB micro SD Card
- Power supply for Raspberry Pi 4
- SD card reader
- x64 PC (laptop or dedicated server)
- USB to RS485 converter (or similar like USB-RS485-WE-1800-BT)
Software
MacOS/Linux based host with installed Docker Desktop
In this milestone, we cover:
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Distributed artificial intelligence
Open Retail Reference Architecture
The AgStack Foundation - https://agstack.org/
Goals
- Start system from scratch with ability to extend it with new services.
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