Using Text-Based and Example-Based Querying to Improve Usage of IoT Sensor Data in Smart Buildings; IoT Devices and Smart Buildings: Starting on the Right Foot

Achieving Industry 4.0: Improving the Use of IoT Device Data in Smart Buildings

Current industrial trends show a push for Industry 4.0 (I4.0) technology. I4.0 is regarded
as the “next industrial revolution” through the use of interconnected technologies. Smart
buildings are a part of I4.0 and utilize Internet of Things (IoT) devices and their data to increase
the efficiency of the operation of their buildings. Both my technical project and my STS research
focus on taking a step towards implementing the vision of I4.0 in the smart building sector. My
technical project proposes an information retrieval solution for smart buildings to solve the
difficulties around managing vast amounts of IoT sensor data. While my STS research stresses
how a lack of infrastructure for IoT device use may result in a hindrance on the journey towards
I4.0.
Buildings are increasing their use of IoT devices to manage their logistics. Because of
this, modern building management systems struggle to utilize the vast and complex data
provided by these devices. In my technical project, I designed and developed a solution that uses
information retrieval techniques to extract information from IoT devices. My solution does this
by requiring the user to form one of two types of queries. They can either query by example or
use a generic text query. Query by example involves the user identifying a graphical trend in
sensor data (e.g. temperature spike) and the system will retrieve other sensor data that exhibits
this trend. Generic text queries are simple keywords strung together that identifies what type of
sensor data the user is looking for. This is similar to questions you would ask in a google search.
Both these queries aim to better capture the search intent of the user. Through these queries, my
system is able to provide a new and different approach to retrieving data for users.Even though the trajectory towards smart buildings seems clear and optimistic, the
involvement of IoT devices requires a robust and secure infrastructure to successfully utilize the
data involved with it. My research navigated various sources on existing I4.0 research and
identified that the lack of infrastructure for IoT device use may impede the success of smart
buildings.
Both of my projects enrich each other by covering the entire scope of the problem
definition. The system I propose in my project solves the difficulty in retrieving vast and
complex data from IoT devices in smart buildings. And, my STS research covers the
sociotechnical aspect of the problem by identifying stakeholder issues that may hinder the
technical achievements of my work. Through this, I have enriched my personal process of
defining engineering problems to not only include a technical aspect but also a sociotechnical
perspective. Additionally, this has led to a restructuring of how I view the responsibilities of
engineers. We, as engineers, are not only here to solve problems using the skills we acquired, but
also are ethically responsible to use our own virtues to push society towards a better place.

School of Engineering and Applied Science
Bachelor of Science in Computer Science
Technical Advisor: Hongning Wang
STS Advisor: Kathryn Neeley
Technical Team Members: Max Zheng