AirQfy Fear Not the Particulates

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between average and value before the previous path of estimation is changed (avoiding jumpsin estimation data). Once a path is chosen the text is updated and the estimation will output avariable that updates across the UI (gauges and charts). Different colours are set to suggest theoccupancy and air quality. In the example given in Figure 14 the air quality is now good but thenumber of people is still quite high. The fan was triggered but as people have been leaving theroom the air quality has been brought back to a good standard.Figure 15 IBM Bluemix showing the registered devices. The 3 ESP8266 MCUs used in 2 light gates and the actuator(Fan) are outlined by the red squareFigure 16 The NodeRED editor showing all the nodes used. IOT device interfaces are circled in red, UI interfacenodes circled in green, Function calculation for the Air Quality approximation in blue.20
Data CollectionData Collection came in two phases. The first part was collecting data via the means of a webscraper. The second phase was creating a dataset from values obtained with hardware sensors.Web Scraper DataThe first testing phase was conducted in the UCL Science Library (4th Floor). Because oftechnical difficulties with counting the number of people entering and leaving the study space, itwas decided to first gather the air quality data and then correlate it with the information that isuploaded on UCL library seating availability website. To collect all the data from the websiteautomatically a web scrapper coded in Python.Figure 17 UCL Library Website presenting the available seats divided by zones. This website was scraped to obtainthe values automatically. (https://www.ucl.ac.uk/library/libraries-and-study-spaces/available-study-spaces )Figure 18 Data Superimposed from 72 hours of scraping. The data was scraped every 5 minutes.21
Page 1 and 2: AirQfyFear Not the ParticulatesTeam
Page 3 and 4: Bibliography ......................
Page 5 and 6: systems lacking in capability to pr
Page 7 and 8: Design BriefProblemThe problem is t
Page 9 and 10: sensors would only need to be used
Page 11 and 12: Creating and Demonstrating the Solu
Page 13 and 14: Table 2 Consumption at ambient temp
Page 15 and 16: Air quality sensor Grove v1.3Figure
Page 17 and 18: Figure 12 Arduino board connected t
Page 19: Figure 14 The final UI for AirQfyIB
Page 23 and 24: The plot above illustrates all thre
Page 25 and 26: Figure 23 MSE error ratesMSE result
Page 27 and 28: The resulting outcome is a hysteres
Page 29 and 30: EvaluatingTesting methods• Air qu
Page 31 and 32: int led_onboard = 13;int threshold_
Page 33 and 34: Serial.println("Gate 1 -> Gate 2");
Page 35 and 36: // delay(1000);//person moves at 1-
Page 37 and 38: int minutes = 3;int hours = 15;int
Page 39: dataString += String(minutes);dataS

AirQfy Fear Not the Particulates

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