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amc2022:grouph:start [2022/09/09 17:11] – [3.5 Deep Sleep Mode and Power Saving] gustavo001amc2022:grouph:start [2023/01/05 14:38] (current) – external edit 127.0.0.1
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 +{{ :amc2022:grouph:schematics_amc.png?nolink&600 |}} 
 +| //**figure 1.1**// Schematics | 
  
  
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 <wrap em> <wrap em>
-How we implemented the DHT-22 sensor into our device is described [[amc2022:grouph:dht22_humidity_temperature_sensor|here.]] +Description of how the DHT22 sensor works can be found [[amc2022:grouph:dht22_humidity_temperature_sensor|here.]] 
  
 </wrap> </wrap>
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 ==== 3.2 Air Particles Measurement ==== ==== 3.2 Air Particles Measurement ====
  
 +Particle Matter are small solid particles and water droplets that are found in air. The size of those particles vary greatly, some we can see with our naked eye, such as pollen, dirt and smoke, while others we need tools like microscopes to detect them. The significance that the presence of those particles have on our health depend on such factors as type of particle, quantity and duration of exposure((https://www.epa.gov/pm-pollution/particulate-matter-pm-basics)). 
 +Due to industrialization and all that it entitles in terms of development, material use and lifestyle, we humans are now more than ever exposed to higher concentrations of harmful particles that are the culprits of multiple diseases.
 +Determining the quality of the air we breath is directly related to knowing how many and what type of those particles are present in the air. Therefore, we have used the MQ2 sensor which not only detects certain types of particle matter but also its concentration.  
 +
 +Listed below are limit threshold amounts for different particulate matter in the air at which the health risks are moderate. There are many sources and depending on where you obtain your source the number may vary. 
 +
 +^Particle ^ Concentration on ppm ^
 +|LPG((www.cdc.gov))                                                                       | 2000|
 +|CO((https://www.myhomecomfort.org/wp-content/uploads/2015/09/CO_Levels_Risk_Chart.pdf))  | 200|
 +|Alcohol((https://www.nj.gov/health/eoh/rtkweb/documents/fs/0844.pdf ))                   | 1000|                                               
 +|CH4((https://www1.agric.gov.ab.ca)).                                                     | 1000|
 +|Propane((https://nj.gov/health/eoh/rtkweb/documents/fs/1594.pdf)).                       | 1000|
 +
 +
 +
 +<wrap em>
 +For an explanation of how the sensor works and how we implemented it in our Air quality device please follow this link [[amc2022:grouph:mq2|MQ 2]]
 +
 +</wrap>
  
  
  
 ==== 3.3 MQTT Database and WiFi Connection ==== ==== 3.3 MQTT Database and WiFi Connection ====
 +
 +In other to connect ESP32 to the MQTT Broker, the ESP32 must be connected to the internet. Since ESP32 supports wifi, it could easily be connected to the local wifi by writing some lines of code on the Arduino IDE. 
 +
  
 To start we use the ESP-32 micro-controller that has very important features, WiFi capabilities to transmit information digitally over any network connection which almost everyone has access to in their houses or workplaces. Additionally, one can connect the controller to a Mobile Hotspot if doing field air quality assessment where no WiFi is available but there is cell phone connection. To start we use the ESP-32 micro-controller that has very important features, WiFi capabilities to transmit information digitally over any network connection which almost everyone has access to in their houses or workplaces. Additionally, one can connect the controller to a Mobile Hotspot if doing field air quality assessment where no WiFi is available but there is cell phone connection.
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 | **//Figure 3//** setup on node-red showing data from mqtt being stored in a data base (influxdb)|  | **//Figure 3//** setup on node-red showing data from mqtt being stored in a data base (influxdb)| 
  
-==== code and explanation ==== 
  
-==== Wifi Connection ==== 
- 
-In other to connect ESP32 to the MQTT Broker, the ESP32 must be connected to the internet. Since ESP32 supports wifi, it could easily be connected to the local wifi by writing some lines of code on the Arduino IDE.  
  
  
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 </wrap> </wrap>
 +
 +
 +
 For the purposes of this project we have selected Deep-Sleep mode. In it only the Real Time Clock **(RTC)** module, which keeps track of time and date in the absence of an external power supply, and the Ultra-Light Co-processor **(ULP)** module which purpose is to perform readings through the __ADC__ and __I2C__ pins, remain active while the main processor is in Deep-Sleep mode as shown in Figure 5. For the purposes of this project we have selected Deep-Sleep mode. In it only the Real Time Clock **(RTC)** module, which keeps track of time and date in the absence of an external power supply, and the Ultra-Light Co-processor **(ULP)** module which purpose is to perform readings through the __ADC__ and __I2C__ pins, remain active while the main processor is in Deep-Sleep mode as shown in Figure 5.
  
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 #define         GAS_SMOKE                     (5) #define         GAS_SMOKE                     (5)
 #define         GAS_PROPANE                   (6) #define         GAS_PROPANE                   (6)
-#define         accuracy                      (0)   //for linearcurves +#define         accuracy                      (0)   //for linear-curves 
-#define         accuracy                      (1)   //for nonlinearcurves, un comment this line and comment the above line if                                                                       \\                                                    calculations+#define         accuracy                      (1)   //for nonlinear-curves, un comment this line and comment the above line if                                                                       \\                                                    calculations
                                                     //are to be done using non linear curve equations                                                     //are to be done using non linear curve equations
  
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 /*****************CALLBACK FUNCTION*************************************************************************************/ /*****************CALLBACK FUNCTION*************************************************************************************/
  
-/****** The mqtt client calls a callback method on seperate thread to main application thread.**************************/+/****** The mqtt client calls a callback method on separate thread to main application thread.**************************/
  
 void callback(char *topic, byte *payload, unsigned int length) { void callback(char *topic, byte *payload, unsigned int length) {
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  Input:   mq_pin - analog channel  Input:   mq_pin - analog channel
  Output:  Rs of the sensor  Output:  Rs of the sensor
- Remarks: This function use MQResistanceCalculation to caculate the sensor resistenc (Rs). + Remarks: This function use MQResistanceCalculation to calculate the sensor resistance (Rs). 
-         The Rs changes as the sensor is in the different consentration of the target+         The Rs changes as the sensor is in the different concentration of the target
          gas. The sample times and the time interval between samples could be configured          gas. The sample times and the time interval between samples could be configured
          by changing the definition of the macros.          by changing the definition of the macros.
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 === Serialboard === === Serialboard ===
-^{{ :amc2022:grouph:serialboard.jpg?800 |}}^ +^ {{ :amc2022:grouph:serialboard.jpg?800 }}  ^ 
-|//**figure #**// | +| //**figure 6**//                           |
  
 === Grafana === === Grafana ===
  
  
-^{{ :amc2022:grouph:group_5_-_grafana.jpg?800 |}}^ +^ {{ :amc2022:grouph:group_5_-_grafana.jpg?800 }}                                     ^ 
-|//**figure #**// Measurement result of DHT22 and MQ2 sensors visualised on grafana|  +| //**figure 7**// Measurement result of DHT22 and MQ2 sensors visualized on Grafana  |
  
  
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 =====7. Conclusion===== =====7. Conclusion=====
  
 +
 +Using a low cost Arduino Kit and integrating the ESP32 micro controller, we were able to accomplish three tasks. The first was to measure different Air Quality parameters such as temperature, humidity and particulate matter. By using the MQ2 sensor, we were able to measure the ppm of the following gasses: H2, CH4, CO, Alcohol, Propane, LPG and smoke. However depending on the source or literature it is possible to find multiple threshold limits of inhalation that produce adverse health effects on humans. Therefore we could further expand the project to have both a more sensitive sensor and a predefined threshold limit that will warn the user of the device of any potential health hazards. As of right now the user is only able to monitor the amount of particulate matter within the scope of the sensor. 
 +Secondly we were able to transmit data using a publish-subscribe broker. By using MQTT we were able to create topics that contained the data received by the Arduino sensors, later with the help of the Node Red software, we created a flow chart in which the data input from the topic and utilizing the JSON format, was sent to Grafana where the data was ultimately transformed visually for easy interpretation. We decided to keep one topic containing all the data, because the idea is to have multiple Air Quality devices running simultaneously but each having its own independent topic. That would help us identify easier any issues with any of the devices. 
 +Lastly we successfully operated the device using a 9V battery and integrated the following components and features for improved performance: 
 +A linear voltage regulator that lowered the voltage to within the 5V usability of the ESP32 micro controller. 
 +A voltage divider that allowed us to measure the battery's charge and continuously kept track of the battery's life, which was also transmitted in the data to the broker for later observation in Grafana.
 +And ESP32's capability of going into deep sleep at our selected time intervals to limit power consumption and to extend the battery's life. 
 +However, we found that the 9V battery was not the best option for this project, but we kept it because it made us integrate components and features that we would not have otherwise thought about using if we have had a more robust and capable battery. 
 +
 +We thus demonstrate that devices with the purpose of monitoring air quality can be built easily and cheaply. In addition, we explained the steps taken by us in this project and expanded on how the components work. We hope that his work can help inspire new students and hobbyists in their pursue of producing devices that have the following characteristics:
 +  * Collection of data
 +  * Programming software
 +  * Transmission of data and usage of brokers
 +  * Electronics
 +  * Reporting through wikis
 +  * FUN!
  
  
amc2022/grouph/start.1662736310.txt.gz · Last modified: 2023/01/05 14:38 (external edit)