# Ensuring Energy Efficiency of Air Quality Monitoring Systems Based on Internet of Things Technology
## 5 Discussion
### Energy Efficiency Estimation of the Proposed IoT Air Quality Monitoring System
Thus, the Ajax LifeQuality sensor is much more energy efficient as it runs on batteries for up to 3 years, consuming 70 times less energy than the Smart Air, while the Smart Air sensor is more functional--it measures more air parameters (PM\({}_{2.5}\), PM\({}_{10}\), TVOC) and offers more integration options, but has higher power consumption. However, the Smart Air sensor is much cheaper compared to the Ajax LifeQuality, which significantly compensates for its annual energy consumption (about 100 UAH/year \(\approx\) USD 2.4/year). To ensure the comprehensive comparison of sensor models, we introduced an integrated efficiency index (_IEI_), which accounts for three key factors: the number of parameters measured (functionality, _F_), energy efficiency (_E_, which is inversely proportional to annual power consumption), and cost (_C_) in USD. The IEI balances functionality and energy efficiency (desirable attributes to be maximized) against cost (a limiting factor to be minimized), aligning with the need for scalable, sustainable IoT systems in smart cities [31; 34]. The _IEI_ is calculated as follows:  
\[IEI=\frac{F\times E}{C}\]  
where:  
_F_--number of measured parameters (e.g., CO\({}_{2}\), PM\({}_{2.5}\), temperature);  
_E_--energy efficiency, defined as 1/annual consumption (kW \(\cdot\) h); and  
_C_--sensor price in USD. In the IEI formula, the parameters F (functionality), E (energy efficiency), and C (price) are given equal weight, as the study seeks to balance three key aspects of sensor selection: their ability to measure various air parameters, their energy efficiency, to ensure autonomy, and their economic feasibility for scaling systems. Their equal weight reflects the assumption that none of these factors is prioritized in the overall context, and the optimal sensor should demonstrate a compromise between all three factors. The equal weighting of functionality (F), energy efficiency (E), and cost (C) in the IEI was chosen to balance the trade-offs that are critical for scalable IoT systems in smart city applications, ensuring that no single factor dominates and providing a practical decision-making tool for diverse stakeholders. While sensor accuracy and data reliability are critical, they were not included in the current IEI to maintain simplicity and to focus on scalability. Future iterations of the IEI could incorporate accuracy as an additional weighted factor to enhance its robustness. For an objective comparison of the most popular sensors, we proposed an integral efficiency index (IEI), which combines functionality, energy efficiency, and price. According to the results of our calculations, the highest efficiency is demonstrated by the Ajax LifeQuality sensor, which, despite its high cost, provides the lowest energy consumption \begin{table}
\begin{tabular}{l l l} \hline \hline
**Characteristic** & **Smart Air** & **Ajax Lifequality** \\ \hline Price & 650 UAH (\(\sim\)16 USD) & 8299 UAH (\(\sim\)200 USD) \\ Power & Permanent USB connection & 3x AAA batteries (up to \\  & (5V, 1A) & 3 years of battery life) \\ Daily Intake & 72 W\(\cdot\)h & \(\sim\)1 W\(\cdot\)h \\ Annual & 26.28 kW & \(\sim\)0.365 kW \\ Consumption & \multicolumn{1}{l}{} & \\ Communication Protocol & Wi-Fi, Zigbee, BLE & Jeweller (energy efficient) \\ Measured & CO\({}_{2}\), PM\({}_{2.5}\), PM\({}_{10}\), TVOC, & CO\({}_{2}\), temperature, \\ Parameters & temperature, humidity & humidity \\ Smart Home & Home Assistant, Google & Ajax Security System, \\ Integration & Home, Alexa & mobile app \\ \hline \hline \end{tabular}
\end{table} 
Table 6: Comparison of the energy efficiency and price of Smart Air and Ajax LifeQuality sensors. (0.365 kW\(\cdot\)h/year) and also has a long battery life (Table 7, Figure 3). Equal weighting simplifies the calculation and interpretation of IEI, which is important for its practical application in real-world projects where complex models may be less convenient [29].