# A Node Placement Algorithm Utilizing Mobile Nodes in WSN and IoT Networks +
## 5 The Energy Node Placement Algorithm
### Energy Models
#### 5.4.1 Moving Energy Model 1  
In [24], [PERSON] et al. model the power consumption of a specific mobile robot. This work presents a model created by experimental results based on different speed and acceleration levels.  
The mobile robot used for this work is a Wifibot [25]. This mobile robot consists of a controllable four-wheel drive chassis, infrared sensor, a web camera, a WiFi adapter, a core, and an embedded system that can be one of the following systems: Linux Ubuntu, NVIDIA, or Raspberry PI, as well as a free WiFi access point. The embedded system of the robot refers to the motherboard where all peripherals are connected to. In order to reduce power consumption, a low consumption power unit and a flash disk are used. A serial port is used for the communication between the embedded computer and the motor board. The role of the motor board is to play the microcontroller and the power regulator. The motor board connects to the power supply, where the power is distributed to the microcontroller and the other components of the robot.  
The experiment setup included a mobile robot (Wifibot), a power analyzer that was connected to the robot, a monitor, and a keyboard. The keyboard was used for the commands and the monitor for displaying the outputs. All experiments took place on a flat surface of a clean non-slipery parquet-style floor, where the robot was protected from spinning or slipping. The models built use different speed and acceleration levels, and the experimental results show the relations between the energy and the speed, as well as the distance.  
A mobile robot's power consumption is the sum of the power consumed by the motors and the embedded devices. The former represents the mechanical power that is used for accelerating and maintaining a constant speed.  
The total energy equation is given below:  
\[P_{total}=P_{e}+P_{l}+P_{m},\]  
where \(P_{e}\) represents the power consumption of the embedded devices, \(P_{l}\) represents the power loss of the transformation from electrical to mechanical energy, and \(P_{m}\) represents the mechanical power and is given by: \(P_{m}=mau+guu\), where \(u\) is the robot's speed, \(m\) is its mass, \(\mu\) is the ground friction constant, and \(g\) is the acceleration of gravity.  
The idea of moving is that the mobile robot starts from its initial position and accelerates until it reaches its maximum speed, where it continues with a constant speed.  
This work divided the recorded power of the mobile robot into two parts: (a) the acceleration power and (b) the power while maintaining a constant speed. Based on this, the total moving energy consumption is calculated with the following equation.  
\[E_{u}=P_{acc_{u}}f_{acc_{u}}+P_{u}\frac{s-s_{acc_{u}}}{u},\]where \(P_{acc_{u}}\) is the power of acceleration at a given speed \(u\), \(s\) is the total traveling distance, \(s_{acc_{u}}\) is the distance traveled during acceleration, \(t_{acc_{u}}\) is the acceleration time, and \(u\) the speed of the robot.  
The results show that the energy cost increases up to 66% when the robot stops frequently due to accelerations. Additionally, at higher speeds, the robot achieved high energy efficiency. Although all results are based on a specific mobile robot, the main conclusion is that acceleration is an action that consumes a high amount of energy, which results in decreasing the operation time of the mobile robot.