View Proposal

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Proposer

Drishty Sobnath

Title

Artificial Intelligence of Things (AIoT) in Smart Cities for indoor air pollution prediction

Goal

Exposure to different pollutants in indoor environments, especially public venues that have a high occupancy and poor ventilation, is a serious public health concern. The main aim of the project is to develop AI models to predict indoor air pollution based on any available public data collected by air quality sensors.

Description

The accelerating convergence of artificial intelligence (AI) and the Internet of Things (IoT) has sparked a recent wave of interest in Artificial Intelligence of Things (AIoT). At this point, most of society understands the issue of air pollution and its repercussions not only on the climate but human health as well. However, not many of us seem to realise that indoor air quality is as important. Unfortunately, indoor air is also susceptible to pollution, and as studies show, its presence can be up to 8 times higher than in outdoor air and most people spend around 80 to 90% of their time indoors. By analysing historical data sets, physical, chemical and biological characteristics of indoor air, different models can be evaluated to predict Indoor Air Quality.

Resources

Python programming, Statistical modelling, Machine learning, PPE, safety, Data Science, Visualisation

Background

Url

Difficulty Level

Variable

Ethical Approval

None

Number Of Students

1

Supervisor

Drishty Sobnath

Keywords

Degrees

Bachelor of Science in Computer Science
Bachelor of Science in Computer Systems
Master of Engineering in Software Engineering
Master of Science in Artificial Intelligence
Master of Science in Data Science
Master of Science in Information Technology (Software Systems)
Master of Science in Software Engineering
Bachelor of Science in Computing Science
Postgraduate Diploma in Artificial Intelligence