Spring school: Smart Sensors, ML and AI: Remote Monitoring during Challenging times - Day#2

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The main focus of 2022 IEEE sensors council's spring school is on smart sensors based remote monitoring which includes health, city and environmental parameters.  The lectures will concentrate on the applications of different sensors as well as intelligent computing (machine learning and AI) and applications of internet of things. The first day will have a series of lectures on the research trends of sensor, machine learning, artificial intelligence and internet of things today and in the future. The 2nd day will be on hands-on experimental activities where the participants will make IoT based system starting from sensors, interfacing to embedded processor, wireless communication, uploading data to cloud, data visualization and machine learning. The 2022 IEEE sensors council's winter school, to be held on September 19-20, 2022 and will be hosted by School of Engineering, Macquarie University, Sydney, Australia.



  Date and Time

  Location

  Hosts

  Registration



  • Date: 20 Sep 2022
  • Time: 09:30 AM to 04:30 PM
  • All times are (UTC+10:00) Sydney
  • Add_To_Calendar_icon Add Event to Calendar
  • 9WW 234/235/237
  • Macquarie University Campus
  • Sydney, New South Wales
  • Australia 2109
  • Building: 9WW

  • Co-sponsored by Prof. Subhas Mukhopadhyay
  • Starts 12 July 2022 01:17 PM
  • Ends 16 September 2022 11:55 PM
  • All times are (UTC+10:00) Sydney
  • 3 spaces left!
  • No Admission Charge






Agenda

 

September 20, 2022

(Room: 9WW 234/235/237, School of Engineering, Macquarie University)

Time

                                Activities

                                          Morning Tea break 9:30am to 10:0am

 

10:00am to 12:00pm

Basic introduction of IoT project. Arduino & Raspberry pi setup and programming it for sensor interfacing. Inter device communication and transmission of data.

 

                                          Lunch break 12:00pm to 1:0pm

 

1:0pm to 2:30pm

Uploading data to cloud using LoRa and WiFi. Development of API.

                                          Afternoon Tea break 2:30pm to 3:0pm

 

3:0pm to 4:0pm

Data Visualization and Machine learning