DATASET
We measure three types of real-time data to provide an insight into the studying/working
environment for users. The noise level is sensed by a MAX9814 sound sensor, converting sound
amplitude into an absolute decibel. The Wi-Fi signal strength of eduroam, which is the most commonly
used network in universities, is scanned by an ESP32 board. The number of people is estimated from
the number of devices scanned by the ESP board.
The sensor and the board are installed in a sensing box. The real-time data with a 4-second interval
is transferred from the sensing box to a separate gauge and a corresponding app through MQTT for
better visualisation, helping users intuitively direct to the information.
DATA DEVICE (Physical)
There are two physical devices for our project: a sensor box and a real-time gauge. We aim
to provide a flexible user experience that
lets users freely choose where to sense the data and where to install the gauge. For instance, users
can install the sensor box in the centre of a shared working environment while placing the gauge in
a spacious area, facilitating everyone to come and see.
The sensor box contains a MAX9814 sound sensor and an ESP32 board to collect real-time data and
transmit it to the MQTT broker. The gauge dial plate indicates the real-time sound level from the
sensor box with a pointer, ranging from 30dB to 90dB. (We can add more details, such as the green to
the red colour of the dial plate.) The LED strip on the bottom of the gauge indicates the Wi-Fi
signal strength. This helps users quickly see if a weak connection is caused by the network or their
devices themselves. Both the progressive colour system (from red to green) and the number of
illuminated LEDs provide immediate visual feedback to users. The LED strip follows the working rule
as below:
- -70 ~ -80 dBm: One red LED light on.
- -60 ~ -70 dBm: Two orange LED lights on.
- -50 ~ -60 dBm: Three yellow LED lights on.
- -40 ~ -50 dBm: Four lime green LED lights on.
- -30 ~ -40 dBm: Five green LED lights on.
By combining noise and Wi-Fi monitoring in a single display, users can make decisions about their studying/working environment intuitively.
DATA DEVICE (Digital)
The app's dashboard consists of three main visual elements. On the top left, we have a
24-hour
historical view of sound and Wi-Fi intensity. Below that, the bottom-left chart shows real-time data
streamed via MQTT over the last minute. In the bottom-right corner, a four-quadrant chart analyzes
the environment to offer study suggestions based on signal and noise levels. Current real-time
values are displayed in the top-right corner of the dashboard, and the estimated number of people in
the classroom is shown on the far left.
HOW TO USE
1. Activate the Dashboard (Scan Marker)
Ensure your phone is connected to the internet (or the specific 'eduroam' network). Then Launch the
app and point your device camera at the designated Target Card (Physical Marker). Ensure the card
is well-lit and fully visible within the frame. The digital dashboard will automatically anchor
itself to the card in the app.
2. Remote Data Monitoring
Once recognised, the dashboard streams live data via MQTT from the fixed sensors installed in the
room. This allows you to remotely visualise the environment's Wi-Fi and noise levels without being
physically next to the sensors.
3. Interact & Inspect Details
Since the dashboard contains dense information, use touch gestures to navigate:
Zoom In/Out: Pinch with two fingers to enlarge the charts and read specific values on the "24-Hour
Overview" or "Environment Analysis."
4. Troubleshooting
Data Freeze: If the real-time charts stop updating or the MQTT connection drops, please restart the
application to re-establish the connection.
Tracking Loss: If the dashboard disappears, simply point the camera back at the Target Card to
regain tracking.
