## 4 Discussion  
To assess the effectiveness of the proposed approach, we calculated the energy consumption of each sensor depending on the level of the intersection of the coverage areas (Figure 3). The interval of change in the level of the intersection of coverage areas was from zero to seven and was in increments of 0.5. The upper limit of the studied interval was experimental. Also, we calculated the number of life cycles of each sensor depending on the level of intersection of the coverage areas (Figure 4) for the values of the level of the intersection of the coverage areas similar to the values in Figure 3. \begin{table}
\begin{tabular}{l l l l l l} \hline \hline \multirow{2}{*}{**Sensor**} & \multirow{2}{*}{**Sensor Coordinates**} & **Optimal** & **Optimal Energy** & **Input** & **Result** \\  & & **Coverage** & **Consumption,** & **Lifecycles** & **Lifecycles** \\  & & **Radius, m** & **mAh** & **Number** & **Number** \\ \hline Sensor 1 & (15; 15) & 6.37 & 40.69 & 57.98 & 240.83 \\ Sensor 2 & (27; 18) & 7.99 & 63.84 & 69.44 & 156.62 \\ Sensor 3 & (30; 35) & 11.27 & 127.06 & 86.80 & 98.37 \\ Sensor 4 & (48; 43) & 10.42 & 108.68 & 66.66 & 138.01 \\ Sensor 5 & (70; 25) & 20 & 400 & 30 & 30 \\ Sensor 6 & (49; 60) & 8.60 & 74.02 & 66.66 & 202.62 \\ Sensor 7 & (80; 50) & 8.92 & 79.67 & 66.32 & 163.17 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Result sensors’ parameters. Figure 3: Energy consumption of each sensor depending on the level of intersection of the coverage areas. Analyzing the obtained results (Figures 3 and 4), we can conclude that the minimum value of energy consumption is achieved in the absence of the intersection of coverage areas. Additionally, in this case, the maximum number of life cycles of sensors is reached. In addition, it can be concluded that achieving the required level of the intersection of coverage areas is achieved by adjusting the coverage radii of sensors 2, 4 and 7 with coordinates (27; 18), (48; 43) and (80; 50), respectively. Adjusting the radii of coverage of other sensors does not allow to achieve the required level of the intersection of the coverage areas of all sensors simultaneously. It is also worth noting that the change of coverage radii and optimization of energy consumption for this network is achieved when the level of the intersection of coverage areas is less than 6.5 m. When comparing the change in energy consumption values for different values of the level of the intersection of coverage areas, we can conclude that using the steamed approach managed to reduce energy consumption by at least 7%. According to Figure 3, the energy consumed by sensor 5 remains constant regardless of the situation of other sensors. This is due to the fact that when changing the coverage radius of this sensor, it is impossible to achieve the required level of the intersection of coverage zones with other sensors, which leads to the lack of a solution to the problem. This also explains the lack of change in the energy consumption of this sensor (Figure 4). We considered the case of two sensors with coordinates (33; 28) and (50; 28) and radii of coverage of 15 m. The minimum coverage radii are \(r_{1}^{min}=3\) and \(r_{2}^{min}=2\). The distance between the sensors is \(l=17\) m. At the level of intersection of the coverage zones \(c=3\) according to Formula (3), the optimal radii of coverage must satisfy condition (17). \[r_{1}+r_{2}=l+c,\ \forall r_{1}\in\Big{[}r_{1}^{min},r_{1}^{max}\Big{]},\forall r _{2}\in[r_{2}^{min},r_{2}^{max}\Big{]}, \tag{17}\]  
In the case of two sensors, the energy consumption function will be a function of two variables \(E(r_{1},r_{2})\), the graph of which is the second order surface. Fixing the value of \(r_{1}=5\) according to Formula (17) at the value of \(l=17\) and \(c=3\), we obtained \(r_{2}=15\). Using the values of \(r_{1}\) and \(r_{2}\), we calculated the energy consumption \(E(r_{1},r_{2})=250\). We constructed  
Figure 4: Number of lifecycles of each sensor depending on the level of intersection of the coverage areas.