Main Page: Difference between revisions
| Line 44: | Line 44: | ||
* [[Smart Cities - First lesson in Python]] | * [[Smart Cities - First lesson in Python]] | ||
* [[Smart Cities - Reading data from Environmental Sensors in an Aquarium]] | * [[Smart Cities - Reading data from Environmental Sensors in an Aquarium]] | ||
* [[Smart Cities - Saving data]] | |||
* [[Smart Cities - Getting to 1 tonne per person by 2030]] | * [[Smart Cities - Getting to 1 tonne per person by 2030]] | ||
* [[Smart Cities - Data Visualisation using the Node-RED dashboard]] | * [[Smart Cities - Data Visualisation using the Node-RED dashboard]] | ||
Revision as of 05:47, 29 March 2022
This web site is an experiment with local students, residents and public agencies to see if participative governance and more open information sharing between agencies can promote healthier waterways in the Whittlesea municipality. In a low carbon and resource constrained future we will all need to explore better methods of engagement and knowledge sharing to protect our communities and the natural environment.
Waterways and Waterbodies in Whittlesea
The main waterways in the Whittlesea municipality include the Plenty river, Darebin creek, Edgars creek and the Merri creek. In addition there are waterbodies (lakes and wetlands) that provide habitat for plants and animals.
- Blau Street Park Bundoora
- Botanica Park lake Bundoora
- Carlingford Park Lalor
- Laurimar Park wetlands Doreen - Lauries Field
- Janefield wetland Bundoora
- Peter Hopper lake Mill Park
Link to Melbourne Water Wetland and Lake Assets. Database helps to identify if a waterbody is managed by Melbourne Water. The database has some errors. Blue shading indicates Melbourne Water asset. Other assets not shaded may be Council assets or private assets.
Smart Cities 2021
The Smart Cities course was offered to students in 2021 at the Whittlesea Tech School. Click on individual lessons below.
- Navigation on the Raspberry Pi
- Security improvements on the Raspberry Pi
- HTML coding
- Adding style to an HTML page using CSS
- Python introduction
- Reading data from an atmospheric sensor
- Saving sensor data to a file
- Saving data with timestamps
- Creating a Dynamic web page
- Scheduling tasks using Cron
- Graphing data using Plotly
- Creating HTML links to Plotly graphs
- More CSS coding
- Requesting data from a Water Quality Sensor in Peter Hopper lake
- Node-RED introduction
- Node-RED data processing
- Node-RED data processing II
- Node-RED creating dashboards
Smart Cities 2022
Term 1
- Smart Cities - What is a Sustainable Smart City?
- Smart Cities - How can we use Environmental Sensors?
- Smart Cities - How to protect the Platypus?
- Smart Cities - Introduction to the Raspberry Pi and Linux
- Smart Cities - First lesson in Python
- Smart Cities - Reading data from Environmental Sensors in an Aquarium
- Smart Cities - Saving data
- Smart Cities - Getting to 1 tonne per person by 2030
- Smart Cities - Data Visualisation using the Node-RED dashboard
- Smart Cities - Transition Engineering
- Smart Cities - Mini-challenge - Soil moisture of a River Red-Gum tree
Term 2
- Smart Cities - Create a Web page in HTML
- Smart Cities - Add Cascading Style Sheets to your web page
- Smart Cities - Creating Dynamic web pages using Python
- Smart Cities - Use Tinkercad to design components for an Environmental sensor
- Smart Cities - Laser cutting and 3D printing using Tinkercad
- Smart Cities - Collecting sensor data from Janefield wetlands
- Smart Cities - Creating a web page for Janefield wetlands
- Smart Cities - Making your web page live on GitHub Pages
Term 3
- Smart Cities - Wetland excursion to Janefield wetlands
- Smart Cities - Exploring analog sensors - turbidity sensor
- Smart Cities - Getting weather data from the Bureau of Meteorology
- Smart Cities - Learn to build and use a Soil moisture sensor
- Smart Cities - Learn to use a distance sensor to measure rainwater tank levels
- Smart Cities - Using Plotly and Python to graph data
- Smart Cities - Customising web sites for mobile devices
- Smart Cities - Adding a Drop Down Menu to a web site
Term 4
- Smart Cities - Discussion about other Smart City Solutions
- Smart Cities - Using data to bring about Change
- Smart Cities - Build a Smart Bee Hive using load sensors
- Smart Cities - Build a Smart Bee Hive using Infra-Red beam sensors
- Smart Cities - Build a Solar hot water shower with a LoRa temperature sensor
- Smart Cities - Build a tiny energy efficient house with a LoRa temperature sensor
- Smart Cities - Grow tomato plants in pots using a LoRa soil moisture sensor
- Smart Cities - Build a hot greenhouse to raise seedlings
- Smart Cities - Build a LoRa GPS litter picker
Sensors
Instructions on how to build individual sensors that can be used in school environmental monitoring projects.
- Temperature sensor
- Pressure sensor
- Distance sensor
- Infra-red beam sensor
- Soil moisture sensor
- GPS sensor
- Turbidity sensor
- Water quality sensor
The Things Network
- Pycom Pygate setup
- How To Register Pycom LoRa Sensors on The Things Network
Sustainable Computers
Simplicity
- Urban Food Production
- The Simplicity Institute - Affiliated with The University of Melbourne
- Happen Films Stories for a Changing World