## 2 Related Work
### Classification by Power Consumption Rate  
As a result of our review, we detected two types of embedded vision systems considering the power consumption rate. They are the following:  
1. Embedded vision system with power consumption rate below 2 watts. 2. Embedded vision system with power consumption rate greater than 2 watts. Tables 7 and 8 present a comprehensive summary of various hardware-constrained embedded vision systems' electrical and power consumption characteristics. The power consumption values were estimated based on the nominal operating voltages and consumption currents under typical operating conditions, providing a reliable basis for comparison. However, it is important to note that these values are subject to change depending on the task and application. For example, image processing and TinyML applications often lead to increased CPU energy consumption due to the high number of mathematical calculations and critical decision tasks. In Tables 7 and 8, devices that do not have a sleep mode function do not consume the nominal operating current all the time. However, depending on the required performance, they can achieve minimum consumptions of up to 10 percent of the maximum operating current rating. Performance depends on the number of critical tasks performed and the computational load of each. In Tables 7 and 8, the Electrical Operating Parameters column indicates the following four important electrical parameters:  
1. Vs: Supply voltage;
2. Idn: Current demand in normal operating mode;
3. Ids: Current demand in very low power mode (deep sleep);
4. Vop: Operating voltage. In applications such as mobile robotics, it is important to know the consumption of the central embedded system for processing and control and what type of battery is the most suitable for each one. Tables 7 and 8 indicate whether the device is compatible with a battery and the type. The types of batteries most used to provide power to the embedded systems listed in the tables are the following:  
1. Lithium-ion battery (Li-ion);
2. Lithium polymer battery (Li-Po);
3. Nickel-metal battery (Ni-MH);
4. Sealed lead-acid battery (VRLA). \begin{table}
\begin{tabular}{c c c c c c} \hline \hline
**Device Name** & **Power Consumption** & \begin{tabular}{c} **Electrical** \\ **Operating** \\ **Parameters** \\ \end{tabular} & \begin{tabular}{c} **Compatibility to** \\ **Battery Use** \\ \end{tabular} & \begin{tabular}{c} **Heat Sink Needs** \\ **Cost in Dollars** \\ \end{tabular} \\ \hline ESP32-S3 & \begin{tabular}{c} Up to 0.3 watts (normal \\ operating mode)/ \\ 0.00068 watts (deep \\ sleep mode) \\ \end{tabular} & \begin{tabular}{c} Vs: 5v, Idn: \\ 68 mA, Ids: \\ 0.000150 mA, \\ Vop: 3.3v \\ \end{tabular} & \begin{tabular}{c} YES/Li-ion, \\ Li-Po, Ni-MH \\ \end{tabular} & NO & 6.50 \\ \hline Arduino Portenta & \begin{tabular}{c} Up to 1.15 watts (normal \\ operating mode)/ \\ 0.00335 watts (deep \\ sleep mode) \\ \end{tabular} & \begin{tabular}{c} Vs: 5v, Idn: \\ 230 mA, Ids: \\ 0.67 mA, Vop: \\ 3.3v \\ \end{tabular} & \begin{tabular}{c} YES/Li-ion, \\ Li-Po, Ni-MH \\ \end{tabular} & NO & 113 \\ \hline Pixy2 (PixyCam2.1) & \begin{tabular}{c} Up to 0.7 watts (normal \\ operating mode)/No \\ sleep mode function \\ \end{tabular} & \begin{tabular}{c} Vs: 5v, Idn: \\ 140 mA, Ids: NA, \\ Vop: 3.3v \\ \end{tabular} & \begin{tabular}{c} YES/ Li-ion, \\ Li-Po, Ni-MH \\ \end{tabular} & NO & 93 \\ \hline PyAI-K210 & \begin{tabular}{c} Up to 1.05 watts (normal \\ operating mode)/No \\ sleep mode function \\ \end{tabular} & \
\begin{tabular}{c} Vs: 5v, Idn: \\ 200 mA, Ids: NA, \\ Vop: 3.3v \\ \end{tabular} &
\begin{tabular}{c} YES/ Li-ion, \\ Li-Po, Ni-MH \\ \end{tabular} & NO & 75 \\ \hline \hline \end{tabular}
\end{table} 
Table 7: Embedded vision system technology with power consumption \(\leq\) 2 watts. Several applications designed for solving tasks that involve real-time image processing, monitoring of critical control actions, and TinyML in mobile robotics systems use low-cost and hardware-constrained embedded systems.