Kauricone Presents: AI/Machine Learning Solutions, Solving dull Tasks

Kauricone Demonstrates, and explains how AI/Machine Learning is used to solve real world problems with Use Case Scenarios

This is your opportunity to learn about the Kauricone AI/Machine Learning Solutions In this session we will provide you with a tour of the Hardware, Operating Systems, Application Software, and how to set up a real world solution using machine learning

WHAT IS MACHINE LEARNING

HOW IT WORKS

WHY USE M/L

HOW WE DO IT

BENEFITS

CHALLENGES

WHAT YOU NEED

What is Machine Learning

Machine Learning is a subset of Artificial Intelligence (AI), that uses technology to collect data and predict the future to help business make decisions

Machine Learning analyses the data collected by applying statistical analysis, and pattern matching, to learn from past experiences. Using the trained data, it provides predicted results

Machine Learning Steps

1. Collect a very large number of images of the object to be detected

2. Annotate each image (ie put a border around each object to clearly identify it from any other object in the same image frame)

3. Identify as many traits of the object as possible

4. Begin training the machine with the objects, and traits that are available

5. Take images of the objects in the production environment

6. Process these images against the trained model at regular intervals

7. Look for exceptions and trends which require action

Predictions

This is the output from the server, after an image has been processed

What you Need

Kauricone TinyML Server (Neural Processor Unit), Cameras (Wifi, 4G,Network,)

ML Application Software

What you will see

How we use images and AI/ ML to identify Building and Construction Waste

How we use images and AI/ ML to identify Burglars on Scooters arriving in Car Parks and stealing from Vehicles

How we use images andAI/ML to identify Rocks on Roads in isolated parts of New Zealand

Click https://kauricone.com/machinelearning to visit Karucone Machine Learning