# Ensuring Energy Efficiency of Air Quality Monitoring Systems Based on Internet of Things Technology
## 5 Discussion
### Architecture of an Energy-Efficient IoT Air Quality Monitoring System
\begin{table}
\begin{tabular}{p{113.8 pt} p{113.8 pt} p{113.8 pt}} \hline
**Risk Category** & **Risk/Challenge Description** & **Decision/Recommendation** \\ \hline Loss of connection with the sensor & Connection interruptions due to a weak signal, interference, or power failure & Placement of Zigbee/BLE repeaters Power supply via Mini UPS \\ \hline Signal instability & Influence of Wi-Fi or radio interference, RSSI reduction \(<-80\) dBm & Selecting free Zigbee channels (25-26) Physical distance between the gateway and Wi-Fi \\ \hline Loss or delay of data & Packets do not reach the controller, or are lost due to collisions or timeouts & Local data caching on ESP or a microcontroller Use of the MQTT QoS protocol \\ \hline Inaccurate data due to environmental conditions & Changes in humidity/temperature affect accuracy (TVOC, PM\({}_{2.5}\)) & Installation of T/RH sensors nearby for compensation \\ \hline Drift or degradation of sensors & Decreased sensor accuracy over time, impact of contamination & Regular calibration (1–2 times a year) Selection of self-calibrating sensors \\ \hline Complete loss of sensor/node & Failure of the sensor or microcontroller (voltage surges, overheating) & Reservation of nodes (duplication of critical areas) Monitoring the status of each device in the software package \\ \hline Incorrect operation of automation & Due to a delay in or omission of CO\({}_{2}\) readings, the ventilation system does not turn on & Setting timers/backup triggers. Checking the last sensor update before action \\ \hline Misinterpretations & Inaccurate visualization on the dashboard, due to gaps in data & Filtering anomalies in the software package Displaying the ’unavailable’ mark if the data are old \\ \hline \end{tabular}
\end{table} 
Table 4: The risks, challenges, and solutions found in distributed air quality monitoring networks. Figure 3: Integrated efficiency index for selected air quality sensors. The Mini UPS acts as a backup power supply. It ensures the smooth operation of sensors and the gateway in the event of a power outage, which is essential to ensure stable air quality data collection, even in conditions of unstable power supply. The collected data are then transmitted to a server or to the cloud, where the information is stored, analyzed, and visualized. The server also performs the function of managing the entire system. Its user interface allows the user to view air quality data, configure the system, and receive notifications when pollution standards are exceeded. The use of Smart Air sensors offers a number of advantages. Thanks to their energy efficiency, long-term battery life without recharging is ensured, which is critical for mobile devices. Reduced power consumption reduces battery replacement costs and also allows the user to increase the number of sensors in the network, creating larger monitoring systems. The energy efficiency of Smart Air sensors is affected by a number of factors. Different types of sensors have different power consumption demands: for example, gas sensors usually consume more energy compared to others. The frequency of measurements is also an important parameter: the more often measurements are taken, the more energy is consumed. The backlight of the display, if present, can significantly increase power consumption. Choosing a wireless protocol such as Wi-Fi, Bluetooth, or LoRaWAN also affects data transfer efficiency. Operating modes, such as sleep or standby, can significantly reduce energy consumption. The energy efficiency of Smart Air sensors is ensured by a number of technical solutions. Software optimization allows the user to minimize power consumption by efficiently managing measurement and data transmission processes. The use of energy-efficient components, such as low-energy microcontrollers and wireless modules, further reduces energy costs. Intelligent power management allows the user to dynamically adjust the voltage and frequency of the processor, depending on the load.