New South Wales

Year 3 – 4

First Place

E.A.S.T (Emergency Alert Sending Technology)
William Moore
Knox Grammar Preparatory School

My project is a sensor that attaches to a bike and can alert emergency services if it detects a crash. It is designed to save the lives of cyclists.

Second Place

Robot Hand
David van Niekerk
Knox Grammar Preparatory School

The Robot Hand is a robotic hand that helps people who cannot grab on to things well. It can also be used as a hand for people who may have lost one. It uses a 3D printed hand with fingers and servo motors to control the fingers. It is coded with a micro:bit.

Third Place

The house with no power points
Hannah Bacigalupo, Misato Heming, Daphne Lai, Isobel Tomlins
Wideview Public School

Imagine a world where there is no such thing as power cords. Where you can move your devices, your TV, your laptop or your lamp anywhere in your house and they will charge or work all the time. Imagine a world where your electric car will charge while you’re driving it. And imagine a world where there are no ugly power poles ruining the view down your street.

Year 5 – 6

First Place

Medibot 3.0
Sol Crisp
St Andrew’s Cathedral School

Two years ago, I created a project called Medibot, a pill reminder system based on voice recognition technology and entered it into YICTE 2020. Last year I built Medibot 2.0 which could run on smaller and cheaper devices, allowed the carer to enter which pills to take and notified the carer when the pills were taken. This year, I will build Medibot 3.0, which will:

  • have a more professional looking user interface
  • record and track if pills are taken
  • allow multiple different pill reminders per day / week

Second Place

Smart Night Light
Alvin Alford, Darrell Sun
Knox Grammar Preparatory School

The Smart Night Light is a Night Light that can be used to detect if a child is not in asleep during the night but is doing something that he/she should not. For example if a light is turned on increasing i.e. the luminosity in a room it would alert parents that their child has woken up. This would encourage the child not to wake up but to stay in bed.

Third Place

Wind Detector
Brya Thackray, Ellie Barron, Charlie Pearson, Tyla Avery
Corrimal East Public School

We are creating a device that alerts you if items have been blown over. We often get very strong winds blowing where we live. Recently there was a large storm in our suburb and a trampoline got blown onto some powerlines, cutting everyone’s power. Bins also often get tipped over, spreading rubbish everywhere and harming the environment.

The device will attach to an item and send out an alarm when it detects that it has tipped over.

Year 7 – 8

First Place

The Plant House
Ethan Qiu, Hayden Chao, Jake Wan, William Hou
James Ruses Agricultural High School

This project is called plant house, which was created by William, Jake, Ethan and Hayden, from James Ruses and Hills Grammar.

Our device was created for efficient space usage in gardens, utilizing Arduino sensors that detect the perfect condition for your plant to live in.The sensor equipped on the device detects soil moisture, humidity, light and temperature. You can control the setting of your plant by changing the temperature, humidity and water needed. The device also self-waters itself to how much you want it to.

The app is a smart way of changing the setting of where your plant is living. There are widgets, information and a Plant profile in the app which tell you how to treat your plants, the information of your plant and changing the setting of the plants living area.

Second Place

SFIStacated Drainage
Indeeka Pinkard, Amelia Carter, Jade Piper, Steph Fleming
Shoalhaven High School

Recently there has been lots of rain making across the Shoalhaven and the whole state terribly muddy. Our idea is to make a technological irrigation system to put into fields to enable kids of all ages to get back onto the fields and keep playing. Our irrigation system will have a moisture sensor which will open up when it senses abnormal amounts of condensation on the field, the pipe will open up and drain the water into a removable water tank that is easily disposable. With an additional mesh plate, that will only let the water through, not the sand.

Third Place

Automatic Wheelchair Ramp Dispenser (AWRD)
Zane Lennox, Tomoki Henderson, Lewis Mackenzie, Cooper Hammersley
Corrimal High School

The NSW train line is one of only a few lines in the world which does not conform to accessibility standards for people in wheelchairs. Each station has a varied height that the platform is below the train doors and this makes it difficult for people in wheelchairs to get onto or off trains on certain platforms.

To get around this the NSW government employs workers with ramps at every station to make them comply with the regulations. This costs the government lots of money and is something the AWRD will fix.

The ramp is a low profile compact deployable ramp that can be retrofitted to the existing train fleet and deploys when the doors open. The ramp deploys in such a way that regardless of platform height it will always deploy correctly allowing wheelchair access and making all stations on the NSW line comply with regulations.

Year 9 – 10

First Place

Pocket Sax
Jesaiah Creek
St George Christian School

Second Place

Declan Hofmeyr, Louis Van liefland, Oliver Jones, Jackson Jones

Chess website and app that allows for creation of Chess variants with JavaScript.

Third Place

PLANeT System – Utilising Artificial Intelligence to Aid Productivity on the Farm
Yuanyuan Guo, Fangfang Guo
Smith’s Hill High School

This project aims to assist crop farmers, particularly family farmers to efficiently carry out crop rotation, estimate annual crop yields and diagnose crop diseases within seconds through artificial intelligence. As opposed to methods such as contacting a plant pathologist which can be both a costly and time-consuming process, the PLANeT system created in this project will provide farmers with a convenient and cost-effective alternative to increase productivity on the farm. This is crucial as drastic changes in the environment are becoming increasingly prevalent due to climate change. With the PLANeT system, farmers can make the most appropriate choices under different and challenging circumstances. These difficulties consist of natural disasters such as droughts and floods, as well as pest and disease outbreaks, and soil degradation. Additionally, the limited support for family farms and the common practice of using pesticides as the ‘one size fits all’ solution has caused detrimental effects on the environment. With this as a motivation, the PLANeT system is developed to focus on the most widely grown and consumed crops in the agricultural industry, including rice, wheat and corn, in which both disease diagnosis and crop yield prediction are specifically tuned for these plants. During the undertaking of this project, a significant problem encountered was inadequate and disorganised data to train the machine learning models, however, through the implementation of data augmentation and additional code to sort the images, this challenge was resolved, and the project was able to run smoothly.