Building an IoT Monitoring App with InfluxDB and LoRa

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This document outlines a workshop for building an IoT monitoring application with InfluxDB and LoRa. The workshop includes setting up an environment with VS Code, a LoRa device, and The Things Network. It then covers connecting the platforms by setting up InfluxDB and Telegraf, developing a custom application for querying and visualizing data, transforming data with downsampling, and creating alerts with thresholds and Slack notifications. The document provides steps and screenshots to guide participants through each portion of the workshop.

Technology

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Workshop: Building an IoT
Monitoring App with
InﬂuxDB and LoRa
February 2022
Jay Clifford, Developer Advocate

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2
Jay Clifford
Developer Advocate, InﬂuxData
● Past life: Sales Engineer for IIoT Solutions
● Passion: OT, Autonomous and Vision based projects
● Driven: To make IoT accessible to all
● Belief: Industrial IoT’s success belongs to the domain
experts.
LINKEDIN
GITHUB

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3
Part 2
Connecting Platforms
Telegraf and InﬂuxDB setup
Part 4
Data Transformation
Creating a Downsampling task
Part 1
Environment Setup
VS code | Device | Things Network
Part 5
Alerting
Create a threshold alert and
notiﬁcation.
Part 3
Custom IoT Application
Querying & Visualization

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4
Background

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Environment Setup

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6
LoRaWAN Microcontroller and Sensors
Temperature
&
Humidity
Soil
Moisture
Light
Soil
Temperature

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7
VS Code Flux Plugin
1. Install Plugin
2. Add InﬂuxDB Instance

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8
The Things Network
1. Add end device
2. Create Payload formatter

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Connecting Platforms

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10
InﬂuxDB Setup
1. Install templates: Plant Buddy &
Things Network

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11
Telegraf Conﬁg
1. Create .env ﬁle
2. Generate Things Network
broker password.
telegraf —debug –conﬁg /path/to/telegraf.conf

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Custom IoT Application

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13
Querying and Visualizing
1. Create a Flux ﬁle
2. Paramatise Fux ﬁle
3. Send Flux Query, transform into
dataframe
4. Visualize with Plotly.

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Data Transformation

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15
Downsampling Task
1. Generate a new task using the
Flux VS Code extension.
2. Aggregate data every 10
minutes

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17
Threshold Alert + Slack Notiﬁcation
1. Create new notiﬁcation task.

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Next Steps

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19
Try it yourself
GITHUB
https:/
/github.com/InﬂuxCommunity/plan
t_buddy/tree/thing_network_demo

| © Copyright 2022, InﬂuxData
Thank you | Any questions?

| © Copyright 2022, InﬂuxData
www.inﬂuxdata.com

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FlowForge enables organizations to reliably deliver Node-RED applications in a continuous, collaborative, and secure manner. Node-RED is the popular, low-code programming solution that makes it easy to connect different services using a visual programming environment. InfluxData is the creator of InfluxDB, the purpose-built time series database run by developers at scale and in any environment in the cloud, on-premises, or at the edge. Jump-start monitoring your industrial IoT devices and discover how to build an edge-to-cloud solution with the MING stack. The MING stack includes Mosquitto/MQTT, InfluxDB, Node-RED, and Grafana. This solution can be used to improve fleet management, enable predictive maintenance of industrial machines and power generation equipment (i.e. turbines and generators) and increase safety practices (i.e. buildings, construction sites). Join this webinar to learn best practices from industrial IoT SME's. In this webinar, Robert Marcer and Jay Clifford dive into: Best practices for monitoring sensor data collected by everyone — from the edge to the factory Tips and tricks for using Node-RED and InfluxDB together Demo — see Node-RED and InfluxDB live

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American Metal Processing Company ("AMP") is the US' largest commercial rotary heat treat facility with customers in the automotive, construction, military, and agriculture industries. They use their atmosphere-protected rotary retort furnaces to provide their clients with three primary hardening services: neutral hardening (quench and temper), carburizing, and carbonitriding. This furnace style ensures consistent, uniform heat treatment process vs. traditional batch-or-belt-style furnaces; excels at processing high volumes of smaller parts with tight tolerances; and improves the strength and toughness of plain carbon steels. Discover why AMP’s use of Telegraf, InfluxDB, Node-RED, and Grafana allows them to gain 24/7 insights into their plant operations and metallurgical results. Learn how they use time-stamped data to gain accurate metrics about their consumables usage, furnace profiles, and machine status. Join this webinar as Grant Pinkos dives into: American Metal Processing's approach to heat treating in a digitized environment through connected systems Their approach to collecting and measuring sensor data to enable predictive maintenance and improve product quality Why they need a time series database for managing and analyzing vast amounts of time-stamped data

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Delft University is the oldest and largest technical university in the Netherlands with 25,000+ students. Since 1999, they have had a team of students (undergraduate and graduate) designing, building, and racing cars, as part of the Formula Student worldwide competition. The competition has grown to include teams from 1K+ universities in 20+ countries. Students are responsible for all aspects of car manufacturing (research, construction, testing, developing, marketing, management, and fundraising). Delft University's team includes 90 students across disciplines. Discover how Delft University's team uses Marple and InfluxDB to collect telemetry and sensor metrics while they develop, test, and race their electrics cars. They collect sensor data about their EV's control systems using a time series platform. During races, they are collecting IoT data about their batteries, accelerometer, gyroscope, tires, etc. The engineers are able to share important car stats during races which help the drivers tweak their driving decisions — all with the goal of winning. After races, the entire team are able to analyze data in Marple to understand what to do better next time. By using Marple + InfluxDB, their team are able to collect, share and analyze high frequency car data used to make their car faster at competitions. Join this webinar as Robbin Baauw and Nero Vanbiervliet dive into: Marple's approach to empowering engineers to organize, analyze, and visualize their data Delft University's collaborative methodology to building and racing their Formula-style race car How InfluxDB is crucial to their collaborative engineering and racing process

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balena.io helps companies develop, deploy, update, and manage IoT devices. By using Linux containers and other cloud technologies, balena enables teams to quickly and easily build fleets of connected devices. Developers are able to use containers with the language of choice and pull IoT sensor data from 70+ different single board computers into balenaCloud. Discover how to use balena.io to automate your InfluxDB deployments at the edge! During this one-hour session, experts from balena and InfluxData will demonstrate how to build and deploy your own air quality IoT solution. You will learn: The fundamentals of IoT sensor deployment and management using balena. How to use a time series platform to collect and visualize metrics from edge devices. Tips and tricks to using balenaCloud to automate InfluxDB deployments and Telegraf configurations. How to use InfluxDB's Edge Data Replication feature to collect sensor data and push it to InfluxDB Cloud for analysis. No coding experience required, just a curiosity to start your own IoT adventure.

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