Application of single chip technology in internet of things electronic products

Abstract

Taking the rapid development of electronic science and technology as an opportunity, MCU which undertakes the equipment control task is developing towards the direction of intelligence, self-learning and multi-function integration. They have been applied to all aspects of human production and life. Driven by computer network technology, the development of Internet of Things technology is promoted. In this era, only by strengthening the research and development and improvement of MCU control system can we promote the development of the entire society and economy. This article mainly studies the application of MCU Technology in IoT electronics. This article first briefly explains the definition of MCU, and then summarizes the entire development process of MCU. On this basis, it is effectively combined with the actual situation, and puts forward the practical application of the MCU Technology in the Internet of Things electronic products. On the basis of ensuring that the personalized needs of modern people are met, it can lay a good foundation for the future development of electronic products. The research experiments in this paper found that up to 70 meters, and found that a large number of packet loss has affected the basic communication. It is believed that communication can be performed at 70 meters but the communication quality is poor. It is not recommended to use, and the test is terminated. It can be seen from the results that the communication distance of the terminal node is finally within 30 meters, which can ensure that the data is almost 100% received. The packet loss rate within 60 meters is within 2%, and the communication quality is good. Guarantee basic communication functions.

Keywords

Internet of things electronic products single chip technology technology research sensor technology

1 Introduction

In recent years, the functions of electronic products have become more and more abundant, the performance has become higher and higher, and the quality of life of people has been significantly improved [1]. The application of these electronic products has greatly improved. It has improved production efficiency in various fields, saved a lot of resources and costs, and made outstanding contributions to the development and progress of society. Among these electronic products, the vast majority of electronic products are developed using MCU Technology, so it can be seen that the MCU Technology is the key to achieving the functions of electronic products. With the rapid development of science and technology, people’s requirements for the functions and performance of electronic products have continued to increase, and electronic products have gradually developed in the direction of intelligence and integration. Only continuous innovation of electronic products can further meet people’s needs, and the application of MCU Technology in electronic products is the only choice to achieve electronic product innovation [2].

In the development process of modern society, the continuous progress of science and technology has promoted electronic products to occupy a very important position in the current social background. This can not only meet the personal needs of modern people for electronic products, but also provide a lot of convenience for the daily life of modern people [3, 4]. Regardless of individual or enterprise development, the application of electronic products can not only improve production efficiency, but also save a lot of human resources, material resources and various costs. It can be seen that electronic products have occupied a very important position in the development of modern society and have made many contributions to the sustainable development of society. During the development of electronic products, it cannot be separated from the application of MCU Technology, which means that the MCU Technology is the key element to realize the functions of electronic products [5, 6].

Delsing J believes that digital hype is increasing the demand for next-generation automation systems. Concepts such as Reference Architecture Model Industry 4.0 (RAMI 4.0) provided him with models, but did not tell him how to facilitate actual implementation. He discussed the transition from legacy automation technologies defined by ISA-95 to highly distributed Internet of Things (IoT) and system-based automation systems (SoS), which take full advantage of Internet technologies to achieve Industry 4.0 and RAMI 4.0 model. Distributed IoT automation systems have many general requirements in terms of real-time performance, security, engineering costs, scalability, and interoperability. To automate the Internet of Things, it is necessary to meet these requirements. A key concept is the local automation cloud. His discussion is based on a special example of such an automated integration platform, the arrow framework [7]. Jun G believes that tension control is a technology widely used in textile, paper, plastic film and other fields. He studied and analyzed the unwinding process of the tension control system, established a mathematical model of the tension control system, and designed a high-performance tension controller [8]. In terms of hardware design, the STM32F130 single-chip microcomputer is used as the control core, which has the characteristics of fast running speed and abundant peripheral functions. In the software design, the μC / OS-II operating system is introduced to improve the efficiency of the microcontroller, increase the independence of each module, and make development and maintenance more convenient. The winding part adopts taper tension control, which effectively solves the problem of rolling shrinkage. His results show that the tension controller has the characteristics of simple structure, convenient operation and stable performance [9]. Cheng Q proposes a composite control structure based on genetic algorithm and intelligent PID, which is difficult for traditional PID control to solve the problems of non-linearity and lag in temperature control systems. A temperature control system is designed with a single chip microcomputer, platinum resistor and TEC cooler as the control processor, temperature sensor and temperature control actuator. He established an intelligent PID control algorithm that dynamically adjusts three parameters of the PID during the control process. He uses the fast search capability of genetic algorithms to optimize control parameters. His experimental results show that the temperature control range of this system is 10°C∼55°C, the temperature control accuracy is±0.03°C, and the overshoot is less than 15%. Therefore, the designed system has a good engineering application prospect [10].

Because nRF24L01 has the characteristics of low cost for easy development, this paper selects it as the main chip for wireless transmission and networking. Based on this, a small wireless sensor with low power consumption and which can be used as a WSN network node [11]. It can be used as a sensing node in the Internet of Things application to provide object information to it, and it can freely and flexibly form a wireless network, which can be applied in the fields of security, logistics, and retail [12]. For example, in the field of security, there are many accidents that occur when the manhole cover is stolen or damaged every year [13]. The wireless sensor under study can be installed inside the manhole cover to monitor the manhole cover in real time and determine whether there is an abnormality. If there is movement, the sensor Report and report to the police, relevant departments can handle abnormal manhole covers in time to prevent safety accidents.

2 About MCU

2.1 MCU definition

MCU is a miniature and perfect computer system integrated in a circuit chip [14]. It is integrated with the help of ultra-large-scale integrated circuit technology. After integration, it is only a small silicon chip. A central processing unit CPU capable of processing data, and also includes a read-only memory ROM, a random access memory RAM, a timer / timer, an interrupt system, and multiple I / O ports. In addition, the silicon chip also includes A / D converter, pulse width modulation circuit, display drive circuit, analog multiplexer and other circuits, these electronic components and circuits are integrated in a small silicon chip, making it a single-chip computer [15, 16].

2.2 Development method of MCU technology in the internet of things environment

(1) Development in the field of monitoring

In the Internet of Things environment, MCU Technology has been widely used, and its development speed is increasing rapidly. In the field of monitoring, the application of MCU Technology can enable electronic products to have monitoring functions, such as vehicle monitoring systems, Smart home system, etc. Taking vehicle monitoring system as an example, the MCU Technology is a core control technology in the vehicle monitoring system [17]. It integrates with communication technology and global positioning system and uses wireless communication networks to carry out passing vehicles. Monitoring can enable the system to automatically receive the vehicle’s positioning data and display it on the map [18 –20].

In addition, users can also issue control instructions through the monitoring center, and implement vehicle management, scheduling, and dynamic tracking functions through a single-chip microcomputer. Nowadays, the development of MCU Technology in the field of monitoring has matured made outstanding contributions [21, 22].

(2) The development of instrument measurement

The development of single-chip computers in the field of instrument measurement is also very fast. The integration of single-chip technology is high and the reliability is good. By integrating the single-chip technology in tiny silicon chips, the accuracy of the instrument can be greatly improved, so that the measurement of the instrument becomes more accurate. And help people solve practical problems with these measurements [23].

(3) Development in the field of industrial control

In the field of industrial control, MCU Technology is the most commonly used technology. Under the IoT environment, the application of MCU Technology to industrial control for data collection and control can achieve automation and intelligent control in the industrial field, greatly improving improved safety in industrial production and improved industrial production efficiency [24 –26].

(4) Developments in the field of electronic communications

In the field of electronic communication, the Internet of Things environment enables people to obtain relevant information about any object and implement data communication with the help of MCU Technology. The development of MCU Technology has also enabled electronic products to perform data in addition to communication functions. Storage, and greatly increase the communication speed and data capacity, greatly promoting the development of the field of electronic communications [27, 28].

(5) Development in the medical field

The emergence of many electronic products has greatly improved the medical level, such as monitors, ultrasound diagnostic systems, and analyzers. These are typical Single-chip electronic products, thereby greatly improving the quality of medical care in China [29 –31].

(6) Development in the field of language recognition

People devote themselves to the development of machine language, which further extends MCU technology to the field of language recognition. Through language synthesis; it can provide greater interpersonal communication convenience [32, 33]. Use of MCU Technology to develop special language processing chips, which can enable it to perform speech synthesis through waveform coding and other technical means, and realize the encoding and decoding of speech signals [34, 35]. These single-chip digital signals are compressed by MCU. Therefore, when needed, these voice data are called, and the voice is restored by reading information, so as to realize the voice communication between human and machine. During the design process, the hardware should be reasonably arranged to reduce the energy consumption. At the same time, try to shorten the processing time of the CPU as much as possible, and reduce the number of applications of the chip as much as possible, and at the same time use the interrupt method to achieve the purpose of low power consumption [36, 37].

(7) Development in the field of automation monitoring

In the field of automatic monitoring, the MCU Technology has greatly satisfied people’s monitoring needs. Nowadays, in the Internet of Things environment, the increasing number of single-chip microcomputer monitoring products enables it to perform various types of sound and light according to different signal types. Alarm and automatic control of equipment startup and shutdown, and can also notify relevant personnel to confirm if necessary [38, 39].

2.3 Calculation method of node position

(1) Trilateral measurement method

The trilateration method is to determine the coordinates of an unknown node based on the distance between multiple beacon nodes and the unknown node [40]. This method requires grasping the distance information of at least three beacon nodes and unknown nodes to estimate the coordinates of the target node [41].

Assuming the coordinates of the unknown node are (x, y), the coordinates of the three known beacon nodes A, B, and C are (x₁, y₁), (x₂, y₂), (x₃, y₃), and their distances to the unknown nodes are d₁, d₂, d₃. According to the distance calculating the formula, you can get the following equations: ${\begin{matrix} d_{1}^{2} = {(x - x_{1})}^{2} + {(y - y_{1})}^{2} \\ d_{2}^{2} = {(x - x_{2})}^{2} + {(y - y_{2})}^{2} \\ d_{3}^{2} = {(x - x_{3})}^{2} + {(y - y_{3})}^{2} \end{matrix}$ (1)

The coordinates of the unknown node can be calculated by Equation (1):

$\begin{matrix} [\begin{matrix} x \\ y \end{matrix}] = {[\begin{matrix} 2 (x_{1} - x_{3}) 2 (y_{1} - y_{3}) \\ 2 (x_{2} - x_{3}) 2 (y_{2} - y_{3}) \end{matrix}]}^{- 1} \\ [\begin{matrix} x_{1}^{2} - x_{3}^{2} + y_{1}^{2} - y_{3}^{2} + d_{3}^{2} - d_{1}^{2} \\ x_{2}^{2} - x_{3}^{2} + y_{2}^{2} - y_{3}^{2} + d_{3}^{2} - d_{2}^{2} \end{matrix}] \end{matrix}$ (2)

As shown in Fig. 1, only when the three circles intersect at one point, the correct coordinates can be obtained through formulas (1) and (2). The disadvantage of the three-sided measurement method is that if the measured distance is different from the actual distance, the three circles will not be able to intersect at one point; there will be a certain error between the coordinates of the solution of the equations and the actual coordinates [36, 37].

Fig. 1

Principle of trilateration.

(2) Triangulation method

The triangulation method uses the cosine theorem to convert the angle of a triangle to the side corresponding to the angle, that is, the angle relationship between nodes is converted into a distance relationship.

As shown in Fig. 2, the coordinates of the three beacon nodes A, B, and C are known as (x₁, y₁), (x₂, y₂), (x₃, y₃) and the included angle of the unknown node D with respect to nodes A, B, and Ccc is ∠ADB, ∠ADC, and DCBDC.. Assume that the coordinates of the unknown node D are (x, y). For the nodes A, B and their angles ∠ADB, when the radian AB is within the triangle OADB, a circle can be determined. Let the center of the circle be O (x_o1, y_o1), the radius be r₁, α = ∠ AO₁B = (2π - 2 ∠ ADB), then the following formula ${\begin{matrix} \sqrt{{(x_{o 1} - x_{1})}^{2} + (y_{o 1} - y_{1})} = r_{1} \\ \sqrt{{(x_{o 1} - x_{2})}^{2} + (y_{o 1} - y_{2})} = r_{1} \\ {(x_{1} - x_{3})}^{2} + {(y_{1} - y_{3})}^{2} = 2 r_{1}^{2} - 2 r_{1}^{2} cos α \end{matrix}$ (3)

Fig. 2

Principle of triangulation.

From the Equation (3), the coordinates of the circle center O and the size of the radius can be calculated. Similarly, for nodes A, C and their angles ∠ ADC and B, C and their angles ∠ BDC, the corresponding circle center O₂, radius r₂ and circle center O₃, radius r₃ can be determined, and then the unknown nodes are calculated using the trilateration coordinate of. The triangulation method is more complicated than the trilateral measurement method. Its core is to measure the angle between nodes. If there is an error in the measured angle, it will affect the accuracy of the final result.

(3) Maximum likelihood estimation method

As shown in Fig. 3, the positioning accuracy of the maximum likelihood estimation method is higher than that of the trilateration method. It needs to determine the coordinates of n beacon nodes such as 1, 2, 3... n and their distance from the target node D to achieve the positioning of the target node.

Fig. 3

Principle of maximum likelihood estimation.

It is known that the coordinates of n beacon nodes such as 1, 2, 3..n are (x₁, y₁), (x₂, y₂), (x₃, y₃)...(x_n, y_n). And their distances from the target node D are d₁, d₂, d₃ . . . d_n, assuming that the coordinates of the target node D are (x, y), then there is a formula ${\begin{matrix} {(x_{1} - x)}^{2} + {(y_{1} - y)}^{2} \\ {(x_{2} - x)}^{2} + {(y_{2} - y)}^{2} \\ . . . \\ {(x_{n} - x)}^{2} + {(y_{n} - y)}^{2} \end{matrix}$ (4)

In Equation (4), the first n-1 equations can be subtracted from the nth equation to obtain.

${\begin{matrix} x_{1}^{2} - x_{n}^{2} - 2 x (x_{1} - x_{n}) + y_{1}^{2} - y_{n}^{2} - 2 y (y_{1} - y_{n}) = d_{1}^{2} - d_{n}^{2} \\ x_{2}^{2} - x_{n}^{2} - 2 x (x_{2} - x_{n}) + y_{2}^{2} - y_{n}^{2} - 2 y (y_{2} - y_{n}) = d_{2}^{2} - d_{n}^{2} \\ . . . \\ x_{n - 1}^{2} - x_{n}^{2} - 2 x (x_{n - 1} - x_{n}) + y_{n - 1}^{2} - y_{n}^{2} - 2 y (y_{n - 1} - y_{n}) = d_{n - 1}^{2} - d_{n}^{2} \end{matrix}$ (5)

Equation (5) can be expressed as a linear equation AX = b, where A is $A = [\begin{matrix} 2 (x_{1} - x_{n}) 2 (y_{1} - y_{n}) \\ 2 (x_{2} - x_{n}) 2 (y_{2} - y_{n}) \\ . . . \\ 2 (x_{n - 1} - x_{n}) 2 (y_{n - 1} - y_{n}) \end{matrix}]$ (6)

After a series of mathematical operations, b is $b = [\begin{matrix} x_{1}^{2} - x_{n}^{2} + y_{1}^{2} - y_{n}^{2} + d_{n}^{2} - d_{1}^{2} \\ x_{2}^{2} - x_{n}^{2} + y_{2}^{2} - y_{n}^{2} + d_{n}^{2} - d_{2}^{2} \\ . . . \\ x_{n - 1}^{2} - x_{n}^{2} + y_{n - 1}^{2} - y_{n}^{2} + d_{n}^{2} - d_{n - 1}^{2} \end{matrix}]$ (7)

The spatial coordinates of the target node D can be represented by X $X = [\begin{matrix} x \\ y \end{matrix}]$ (8)

The standard minimum mean square error estimation method can be used to determine the coordinates of the target node D as $X = {(A^{T} A)}^{- 1} A^{T} b$ (9) (4) Positioning based on RSSI

The RSSI-based positioning algorithm is a positioning method that converts signal strength into distance. In general, the RSSI value of a node’s signal will decrease as the propagation distance increases. Generally, the longer the distance between nodes, the weaker the signal reception strength [42]. The RSSI ranging process is: beacon nodes transmit signals of the same power, and pass the location, node identification, etc. to other nodes: unknown nodes collect the signal strength from the beacon nodes: the RSSI measurement value is substituted into the path loss model to calculate the beacon the distance from the node to the unknown node. Under ideal conditions, the distance between nodes measured by RSSI is the same as the real physical distance, and it can accurately locate unknown nodes. However, in practical applications, obstacles, humidity, weather and other factors will cause changes in signal-related parameters, resulting in large RSSI ranging errors [43]. The path loss model is as follows: $PL (d) = PL (d_{o}) - 10 M {log}_{10} \frac{d}{d_{o}} + x_{σ}$ (10)

In the formula, d represents the distance between nodes: d. Represents the reference distance, generally considered d_o = 1m, PL (d), which indicates the strength of the signal received at the distance d from the transmitting end: PL (d_o) indicates the strength of the signal received at the signal propagation distance at d_o: M represents the path loss index, which needs to be adjusted according to the actual situation. ∼ 4.5; X_σ represents a Gaussian random noise variable with a mean of 0 and a variance of σ². Among them, the size of PL (d_o), can generally be obtained from experience or from the hardware description, while formula (10) can be further simplified as: $RSSI = - [A + 10 M {log}_{10} d]$ (11)

In the formula, RSSI = PL (d); A = PL (d_o), the value ranges from 45 to 49. The distance between nodes is calculated by the formula, $d = 10^{\frac{- A - RSSI}{10 M}}$ (12)

It can be known from formulas (10)–(12) that noise interference and unreasonable path loss index will affect the RSSI ranging results.

3 Process of experiment

3.1 Power test

The base station module is generally connected to a computer through a USB interface and is powered by the computer, so there is no requirement for power consumption. Next, the power consumption test of the sensor terminal node is performed. The sensor terminal node wakes up every 10 s to query the value of the acceleration sensor. If there is no new acceleration information, it enters the sleep state again. If there is a new acceleration value, it enters the sending state, sends the acceleration value to the base station, and sets it to Wake up every 1 s to query the acceleration value, then send and sleep until the acceleration value of the acceleration sensor is zero, that is, when the sensor terminal node is stationary, it is set to wake up every 10 s.

3.2 Communication ability test

Use the serial port debugging assistant to receive the data transmitted by the terminal node to the base station. In order to test whether the transmitted data and the received data are consistent, set the transmitted data in the terminal node software program to a fixed value. The received data and fixed values displayed on the serial port debugging assistant can know the correctness of the sending function of the node. By changing the fixed value multiple times and conducting multiple experiments, the accuracy of the test results is guaranteed. In these experiments, the distance between the terminal node and the base station is not very far. For the convenience of testing, the distance is set to within 2 meters. The fixed value settings are shown in Table 1. Each data is sent twice.

Table 1
Sending data able

Data

0x01 0x02 0x03 0x04 0x05 0x06 0x08 0x02 0x03 0x04 0x05 0x06

0x020x02 0x03 0x04 0x05 0x06 0x09 0x02 0x03 0x04 0x05 0x06

0x03 0x02 0x03 0x04 0x05 0x06 0x10 0x02 0x03 0x04 0x05 0x06

0x04 0x02 0x03 0x04 0x05 0x06 0x11 0x02 0x03 0x04 0x05 0x06

0x05 0x02 0x03 0x04 0x05 0x06 0x12 0x02 0x03 0x04 0x05 0x06

0x06 0x02 0x03 0x04 0x05 0x06 0x13 0x02 0x03 0x04 0x05 0x06

0x07 0x02 0x03 0x04 0x05 0x06 0x14 0x02 0x03 0x04 0x05 0x06

Data
0x01 0x02 0x03 0x04 0x05 0x06	0x08 0x02 0x03 0x04 0x05 0x06
0x020x02 0x03 0x04 0x05 0x06	0x09 0x02 0x03 0x04 0x05 0x06
0x03 0x02 0x03 0x04 0x05 0x06	0x10 0x02 0x03 0x04 0x05 0x06
0x04 0x02 0x03 0x04 0x05 0x06	0x11 0x02 0x03 0x04 0x05 0x06
0x05 0x02 0x03 0x04 0x05 0x06	0x12 0x02 0x03 0x04 0x05 0x06
0x06 0x02 0x03 0x04 0x05 0x06	0x13 0x02 0x03 0x04 0x05 0x06
0x07 0x02 0x03 0x04 0x05 0x06	0x14 0x02 0x03 0x04 0x05 0x06

The data in Table 1 are the data sent by the terminal node during the test. Each data is sent twice. 14 different fixed data are set in turn and 14 experiments are performed. The data can be clearly seen that the data was received correctly every time. This result confirms that the wireless transmission function of the terminal node can be realized and the accuracy of data transmission can be guaranteed.

3.3 Communication distance test

The test program of the terminal node is set to always send the same data, and the data length is set to a maximum of 32 bytes. In actual communication, the length of the data packet will not be so large. In the test, the base station is fixedly connected to the laptop, and the received data is displayed on the serial port debugging assistant. The communication distance is tested by moving the sensor terminal. The test environment is a football stadium and a building aisle, and data packets are sent 100 times at a time.

4 The test data

4.1 Experimental analysis

(1) Power test analysis

In the experiments of this paper, the system’s working current is not easy to measure, so it is divided into two ways to measure, one is to keep the sensor terminal in the sleep state, and the other is to keep the sensor terminal in the sending state, which is the motion state. Multiple measurements were taken in each of these two states. The test data is as follows:

As shown in Table 2 and Fig. 4, the average current consumption of the sensor terminal node under normal operating conditions should be in the uA level, and such power consumption can still meet the requirements. Of course, if the sensor terminal node is always in motion, its current consumption will reach the level of m A. However, in general applications, it is impossible for a sensor terminal node to be in a moving state for a long time, so in actual applications, it can be guaranteed that the battery will not be replaced for a long time.

Table 2
Power test data able

The serial number Sending current(m A) Resting current(uA)

1 21.4 3.8

2 20.7 3.5

3 20.2 3.5

4 20.3 3.5

5 20.4 3.6

The serial number	Sending current(m A)	Resting current(uA)
1	21.4	3.8
2	20.7	3.5
3	20.2	3.5
4	20.3	3.5
5	20.4	3.6

Fig. 4

Power test data.

(2) Analysis of communication distance test

As shown in Table 3 and Fig. 5, the test environment is divided into the building aisle and the football field, and the test is performed in different environments. In the test of the building aisle environment, the computer connected to the base station is fixed at one end of the aisle, and the terminal node is 10 meters away. The location has been moved to 50 meters. Due to the limitation of the building structure, the distance after 50 meters is not tested. Then the computer and terminal nodes are transferred to a wider outdoor football field environment for testing, starting from the aisle test. The test was started at a distance of 30 meters for packet loss, and it increased by 10 meters each time to 70 meters. It was found that the number of lost packets was large, which had affected the basic communication. It was determined that communication was possible at 70 meters but the communication quality was poor. It is not recommended Use, and terminates the test. It can be seen from the results that the communication distance of the terminal node is finally within 30 meters, which can guarantee almost 100% data reception, the packet loss rate within 60 meters is within 2%, and the communication quality is good. Basic communication functions are also guaranteed.

Table 3

Test results able

Test environment	Communication distance(M)	Number of dropped packets	Test environment	Communication distance(M)	Number of dropped packets
Building walkway	10	0	Football field	30	0
Building walkway	20	0	Football field	40	1
Building walkway	30	1	Football field	50	1
Building walkway	40	1	Football field	60	2
Building walkway	50	2	Football field	70	5

Fig. 5

Comparison of test results.

(3) Anti-interference test analysis

The frequency band where the node works is the international frequency band. In the same frequency band, there will be many other nodes communicating with each other, and there will be some interference. The most important is Wi-Fi interference. The test is performed under the conditions of turning on Wifi interference indoors and turning off Wifi interference indoors. The test results are shown in the table below.

As shown in Table 4 and Fig. 6, when testing for Wifi interference, the wireless Wifi interference signal source in the room close to the aisle is turned on. After the mobile phone network test, the Wifi interference signal can be covered by the aisle, and then each time In the test, data packets were sent 100 times, and the packet loss rates at different distances were counted. When there was no interference, all indoor wireless Wifi interference signal sources were turned off, and the mobile phone network test was performed to verify that there was no Wifi signal, and then the test was performed. After comparison, the impact is not large, and it will not cause a significant decrease in communication quality. The test results can show that the nodes designed in this paper can also guarantee higher communication quality in the presence of interference.

Table 4

Test results able

Test environment	Communication distance(M)	Number of dropped packets	Test environment	Communication distance(M)	Number of dropped packets
Open Wifi	10	0	Turn off Wifi	10	0
Open Wifi	20	1	Turn off Wifi	20	0
Open Wifi	30	2	Turn off Wifi	30	1
Open Wifi	40	2	Turn off Wifi	40	1

Fig. 6

Comparison of test results.

4.2 Application analysis of MCU technology

(1) The effective application of MCU Technology in the monitoring of electronic products

In the context of the continuous advancement are being developed and utilized, bringing a lot of convenience to the daily life, study and work of modern people. Among them, the high-intensity development and utilization of electronic products can play a very important driving role for modern people and modern enterprises in the development process, and MCU Technology in electronic products is an indispensable part of it. By analyzing the actual application of the MCU Technology, it can be seen that this technology has a very important influence in electronic products of the Internet of Things.

As shown in Fig. 7, as the scale of the Internet of Things industry gradually increases, the demand for electronic products will also increase. The MCU Technology has an important influence on the monitoring of electronic products, so it is widely used. When the technology is applied, it can ensure that people can meet the basic needs of monitoring certain things to the greatest extent. When constructing the vehicle monitoring system, global positioning and communication technologies are effectively combined. At the same time, MCU Technology is used as the core control technology. On this basis, the wireless communication network is used to monitor and control the vehicle in real time and effectively. In this way, the monitoring center can not only analyze the actual situation of the vehicle in time, but also use the data obtained by the monitoring center to track the vehicle’s movement And status monitoring.

Fig. 7

The huge scale of application market segments in the IoT industry.

(2) The effective application of MCU Technology in the measurement of electronic products

The MCU Technology is widely used in the measurement of electronic products and instruments. In the application process, the advantages and characteristics of the MCU Technology can be brought into full play. MCU is relatively small in size, and at the same time has high reliability, and also has the characteristics of high integration. Therefore, its application to the measurement of electronic products can help improve its accuracy. At the same time, it can also effectively control electronic products in practice. For example, the scientific and reasonable application of the MCU Technology to the aviation field can not only achieve effective measurement of electronic products, but also ensure the accuracy and validity of the measurement results to the greatest extent. Measurement can provide accurate and effective data basis for people’s series of decisions as support. At the same time, people can also effectively judge the occurrence law and degree of accidents based on these data and information, so as to avoid space accidents as much as possible.

(3) The effective application of MCU Technology in the industrial control of electronic products

The Internet of Things technology is relatively common in industrial control at this stage and has gradually become an inevitable development trend. Under this prerequisite, the application time of MCU in the industrial field is also earlier, especially the advantages and characteristics of MCU technology in industrial control can be brought into full play. In the industrial control process, the use of MCU Technology can help promote electronic products with very powerful data acquisition functions, and also can achieve good control functions. At the same time, in the industrial control process, according to the actual situation, specific requirements can be combined to effectively integrate MCU Technology with the computer. In this way, not only can the overall utilization rate of the MCU Technology in industrial control be fundamentally improved, but also it can help to promote the electronic products with secondary control functions and alarm functions to display their functional features. In this way, on the basis of providing basic protection for the personal safety of staff, it can ensure that it can play its fundamental role even in the face of some environments with relatively severe risk factors.

(4) Practical application of MCU Technology in communication of electronic products

With the continuous development and progress of modern science and technology, China has entered the era of information and network, and more relevant technologies have been applied to all walks of life. Driven by this big environmental background, more and more electronic products are promoted, which can have a great impact on people’s daily lives. Through detailed analysis of these electronic products, it can be seen that the scientific and reasonable application of the MCU Technology in electronic products can promote the development of the communication functions of the electronic products themselves, and can achieve good application results in practice. There is a communication interface in MCU, and the communication interface can be used to realize data communication between the electronic product and the computer, and effectiveness of the data in the transmission process. In addition, the reasonable utilization of single chip microcomputer technology can promote the development and utilization of the network communication function of electronic products. The application of MCU Technology is conducive to improving the communication speed of electronic products. It can not only provide protection for the increase of the data storage volume of electronic products, but also promote the continuous optimization and improvement of communication functions of electronic products in practice. Its intelligent, convenient and fast features are fully utilized.

5 The role of MCU technology

Countries around the world are vigorously developing the Internet of Things. This article designs and implements a miniaturized low-power application that can be applied to smaller networks and fewer nodes. Wireless acceleration sensor. The test results show that the design basically realizes the required functions, can meet the needs of wirelessly detecting the acceleration information of the object, and the reliability of data transmission is better within a certain range.

The research in this article considers that the application of the MCU Technology to the Internet of Things electronic products can not only promote the intelligent synthesis of speech in electronic products, but also develop the communication and control functions of the electronic products themselves. At the same time, the reasonable application of MCU can be effectively combined with other new technologies. On the basis of ensuring a good future development trend of the Internet of Things electronic products, it can continuously expand its application and development scope.

With the advent of the era of big data intelligence, data has become a means of production. How to transform it into productivity requires innovative business models and in-depth research on information technology. In different industries and fields, when the same resource capacity is owned by different stakeholders, the opportunity cost is different. The resource capacity should be allocated to stakeholders that can play a more efficient role to achieve the value-added of the entire transaction structure. It is a rational choice for economic analysis to have engineering enterprises takes on this part of social responsibility for information development, so that the benefits they realize are greater than the opportunity costs. The application of big data has brought changes in business models to many industries. For example, the Internet industry is very dependent on big data technologies. Although the business model innovation mentioned in this article has its economic analysis support, in the field of engineering construction, people still need to go through the process from integrating data, understanding data, and then applying big data.

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Application of single chip technology in internet of things electronic products

Abstract

Keywords

1 Introduction

2 About MCU

2.1 MCU definition

2.2 Development method of MCU technology in the internet of things environment

2.3 Calculation method of node position

3.1 Power test

3.2 Communication ability test

4 The test data

4.1 Experimental analysis

Table 2 Power test data able The serial number Sending current(m A) Resting current(uA) 1 21.4 3.8 2 20.7 3.5 3 20.2 3.5 4 20.3 3.5 5 20.4 3.6

References

Table 2
Power test data able

The serial number Sending current(m A) Resting current(uA)

1 21.4 3.8

2 20.7 3.5

3 20.2 3.5

4 20.3 3.5

5 20.4 3.6