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In order to cut manual labor for flowers cultivation and improve flower survival rate, a multi-functional cultivation system is designed to realize the smart cultivation, maintenance and ornamental value of flowers. The system, centered on STM32 single-chip microcomputer, conducts judgement and treatment of environmental data collected by sensors and simultaneously displays on LCD screen. The cultivation system integrates the Internet of Things and speech recognition technology, which can monitor and control through the remote-control terminal, and control the flower rotation, atmosphere lamp switch and other interesting ornamental functions through the voice module.

In order to detect metal objects, ldc1314 sensor is used, which is based on the principle of eddy current. When a metal object is close to the sensor, the inductance L will change due to mutual inductance, which will cause the frequency change in the oscillation circuit LC. It is converted into digital quantity and output to microprocessor by IIC interface. The microprocessor can process it and perceive metal objects. Effective distance up to 10 cm.

Gesture remote control pick-up car is divided into remote control part and car part. The remote-control part can set the control type, capture the hand posture, display data and transmission data; the car part captures the manipulator's posture and display data, and calculates and controls by receiving the hand data. Make the manipulator and man's hand posture consistent, and also can control the car's driving by the man's hand posture. The manipulator is made with a 3D printer and uses a steering gear as a power device with three degrees of freedom. Use the STM32 series microprocessor as the control chip, read the data from the attitude sensor, perform calculation and filtering, solve the attitude, and achieve remote object retrieval by controlling peripheral devices.

This paper investigated the application of unsupervised learning on a mainstream microcontroller, like the STM32 F4. We focused on the simple K-means technique, which achieved good accuracy levels on the four test datasets. These results are similar to those obtained by training a k-nearest neighbor (K-NN) classifier with the actual labels, apart from one case, in which K-NN performs consistently better.

The paper is focused on the possibilities of using high-level language - Python in the development of IoT applications. Described are the basic features of the MicroPython implementation and its use in the development of peripherals on the STM32 class microcontroller platform, as well as the possibilities of modification and extension of the standard implementation. Further are mentioned terms of code portability, modularity, flexibility, scalability and expandability significant for MicroPython applications.

This paper presents a portable license plate recognition system based on single chip microcomputer with the off-the-shelf mini camera. The system hardware mainly consists of STM32 single-chip microcomputer and the image acquisition sensor OV7670. A TFT color screen is adopted for real time image display and AMS1117 is used for the power conversion and supply. The system uses STM32 MCU to control the overall operation of the license plate recognition system, and controls the mini camera to perform image acquisition through the jump-point analysis and image binary processing method, and then locates the license plate area. With the plate characters successfully localized, the recognition of the license plate is finally obtained through the character segmentation and matching. The experimental results have shown that our system has the best performance under normal light, when the inclination is less than 15° and the character integrity is more than 85%.

The paper presents an analysis of the realization of digital signal processing algorithms with the use of STM32F4 microcontrollers. Various programming techniques have been demonstrated focusing on the implementation of FIR filters and FFT calculations based on Cortex Microcontroller Software Interface Standard. During the tests we use STM32F407 Discovery module with WM5102 Wolfson Audio Card. The speed of algorithms and the accuracy of calculations were checked. The quality of digital filters were tested using LMS adaptive filter or Analog Discovery 2 device.

To accurately detect the location of moving targets. Eight photoelectric sensors ST188 are arranged in a row. When an object passes directly above it, the output voltage of ST188 will change obviously. The voltage is connected to the A/D acquisition pin of STM32 to determine the position of the object according to the change of voltage. By adding a photosensitive detection circuit, the threshold of voltage detection can be adjusted in real time to achieve intelligent control. By introducing Bluetooth module, the communication between multiple detection modules can be realized, and a photoelectric sensor array can be formed to achieve a wider range of position detection. The test results show that the sensor module can detect the position of moving objects accurately and quickly, and has certain practical value.

Home lighting has always played a very important role in people’s quality of life. How to make home lighting more humane is the trend of future development. This article designed a lighting control system that can be controlled by speech. The system receives the voice signal from the microphone, then uploads the voice signal to the server through the Raspberry Pi. The system uses the speech cloud service to identify and analyze the speech signal. The result of speech recognition is transmitted to the STM32 by the Raspberry Pi. STM32 controls single lamp or multiple lamps according to the recognition result. Since the speech cloud provides semantic analysis services, our speech instructions are less restrictive and more closer to everyday language. This system realizes the function of far-field identification and control linkage, while getting rid of the dependence on mobile phones, and the lighting control mode is more humanized.

IoT end-user devices are attractive and sometime easy targets for attackers, because they are often vulnerable in different aspects. Cyberattacks, started from those devices, can easily disrupt the availability of services offered by major internet companies. People that commonly get access to them across the world may experience abrupt interruption of services they use. In that context, this paper describes an embedded prototype to classify intrusions, affecting TCP packets. The proposed solution adopts an Artificial Neural Network (ANN) executed on resource-constrained and low-cost embedded micro controllers. The prototype operates without the need of remote intelligence assist. The adoption of an on-the-edge artificial intelligence architecture brings advantages such as responsiveness, promptness and low power consumption. The embedded intelligence is trained by using the well-known KDD Cup 1999 dataset, properly balanced on 5 types of labelled intrusions patterns. A pre-trained ANN classifies features extracted from TCP packets. The results achieved in this paper refer to the application running on the low cost widely available Nucleo STM32 micro controller boards from STMicroelectronics, featuring a F3 chip running at 72 MHz and a F4 chip running at 84 MHz with small embedded RAM and Flash memory.

In view of the increased fire hazards, the fires in the places of high-rise buildings and crowded have caused work burdens on firefighters due to various factors, resulting in failure to rescue in time in recent years, this paper studies the four-rotor fire-extinguishing system for fire-fighting air-ground synchronous monitoring. The system is divided into two parts: the air-ground communication positioning navigation system based on STM32 core processor and the fire detection and fire-extinguishing system based on STC89C51 core processor, the two parts realize the functions of four-rotor obstacle avoidance navigation, information positioning, ZigBee wireless communication, fire detection, and fire extinguishing device startup. The design of this system makes the fire hazard greatly reduced, achieves real-time communication and positioning navigation more smooth, it’s applicable to urban community high-rise building security, large-scale shopping mall fire, forest orchard fire and other natural disaster fire facilities.

The connection of different modules from different manufacturers into a single bus for the exchange of data and control is a challenge for the agricultural machinery industry using ISO 11783 standards (called ISOBUS in the market). It shows strong potential to become the de facto standard for the exchange of data between modules on the agricultural tractor. This research presents the development of an ISOBUS monitoring system and virtual terminal (VT) for agricultural vehicles. The graphical user interface (GUI) of VT is developed on the embedded system by using the Qt with cross-platform for an ARM Cortex-A9 microprocessor named by Freescale i.MX6 Quad. The GUI application programs were developed based on the Isocore-suite commercial library by the OSB AG Engineering company and certified by the Agricultural Industry Electronics Foundation. The implemented electronic control units (ECUs) and ISOBUS monitoring system were developed by the ISOAgLib open-source library, in addition to tools such as the vt-designer, the vt2iso, the CAN server, the CAN messenger, and the CAN logalizer. The implementation of ISOAgLib is fully compatible with the ISO 11783 standard. The hardware implementation is the development board for the STM32 ARM Cortex-M3 microcontroller. The implemented ECUs were experimentally tested on the ISO 11783-compliant intelligent monitoring system AFS Pro 700 for the New Holland Agriculture tractor. Also, we simulated VT-Server and implemented the sprayer, the manure spreader, the global positioning system modules with the Kvaser PCIe CAN device, and PCAN-USB device in order to analyze all CAN messages and network protocols such as the transport protocol (TP), extended transport protocol (ETP), address claiming, and request parameter group number (PGN) messages. Finally, we present an ISOBUS object pool (IOP) binary file from the implemented ECU and an interpretation of IOP files shown on the CONLAB-VT.

This design is a control system that uses a series MCU of STM to control the small ball can run along the specified track to the destination point and stable. It is used STM32F407 and STM32F103 as a control center for the control of signal acquisition and control of the steering wheel. The STM32F407 and the camera OV7670 form the information collection system module. The information that is collected is processed coordinate former by STM32F407, which is sent to another to receive the Bluetooth module by Bluetooth. Then the coordinates are received by STM32F103, which controls the rotation of the two steering gears according to the coordinate information. To control the rigid ball in accordance with the specified trajectory movement and to reach the specified time of stay. When the ball reaches the specified coordinates, use the Positional PID control to stabilize the ball at the specified point.

This design develop an energy consumption acquisition system based on narrowband Internet of Things using stm32 series low-power microcontroller stm32f407 produced by STMicroelectronics [1]. The system consists of Perception layer, Network layer, and Application layer. The Perception layer includes an intelligent collection terminal. The Network layer upload data to the server through Low Power WAN. The Application layer achieve intelligent monitoring of remote nodes. The system not only meets the requirements of acquisition and transmission in industrial environments, but also can be applied to terminal data collection and transmission requirements in many different networks such as building networks and home networks. The system hardware design adopts the modular circuit design method, which mainly includes: the minimum system board of the microcontroller, the power management module, the clock circuit module, the data storage module, the narrow-band IoT module. The system software design adopts the service-level hierarchical programming idea. For the different modules, write the corresponding driver code; according to different protocols, write the corresponding communication protocol code. Since the design is based on industrial control site requirements, the system uses industrial design standards. The system runs well and is suitable for two-way remote meter reading system in industrial control field.

A pipeline leakage signal acquisition and processing system based on STM32 and LabVIEW have been designed. In this system, the STM32F103RBT6 is used as the lower computer and processing chip. The signal data was transferred to host computer by ZigBee wireless transmission module. In the host computer, a set of signal acquisition and processing system is designed based on the LabVIEW development platform. The software system can be used in conjunction with MATLAB software. In addition, after every static time the master computer will send the command to make slave computer refresh machine time by GPS modules.

This study involved selecting parameters for a PID controller and a fuzzy logic controller employed to control an electropneumatic servodrive. The fuzzy logic controller was a multiple input single output (MISO) system with two inputs and one output. 25 MacVikar-Whelan rules were the rule base of the fuzzy logic controller. The minimum T-norm and the maximum T-conorm were the implication and aggregation operators, respectively. The defuzzification process was conducted using the center of gravity method (COG). The control algorithms were implemented in a speedgoat hardware and software real time system and a STM32 microcontroller. The performance of the control systems was assessed by comparing the values of the performance criteria. Responses to step and pulse input signals in shift control and ramp and sine input signals in follow-up control were also analyzed. The experimental data show that further research is required on this topic.

Most smart home products on the market today only stay at the level of multi-channel control of home appliances and have a single product function. For those parts that are not involved, this article describes a smart home cloud system based on Kinect. The system uses the STM32 as the control core and utilizes Kinect depth sensors to establish an identity and posture recognition system based on human skeletons, combined with support vector machine (SVM) and Internet of Things technology to realize smart home control systems. What is more, intelligent alarm system and child anti-drop window control system truly realize home Intelligence. After verification, the system can greatly improve the current level of intelligent home security capabilities, make up for the vacancy of the existing identity system, real intelligence for the home rather than intelligent control of home appliances is finally achieved.

With the rapid increase of the retain quantity and service time, pipeline leak detection and leak location problem have gotten extensive attention. In order to monitor the industrial pipeline, this paper develop a distribute pipeline leakage signal acquisition and processing system based on Zig Bee. In this system, STM32 microcontroller is the core and Wireless sensor is the network node. LabVIEW is used in PC as the monitor. The data transmit by Zig Bee wireless network between the upper and lower computer. Cross-correlation operation is used as the Leak location algorithm. Correlation analysis of the four sensor output signals is executed. This method eliminate the measurement error caused by the change of sound wave propagation speed, and further improved the positioning accuracy.

With the ultimate goal of cost reduction of condition monitoring, this paper illustrates how simple data acquisition and processing systems could be designed and realized taking advantage of latest cheap, yet powerful electronic elements. The discussed designs are based on recently popular STM32 and Raspberry Pi boards, and analog MEMS accelerometers. The final prototype design shown in the paper is developed on the F401re version of the STM family, which is working on ARM M4 Cortex processor, and the ADXL001-70 MEMS accelerometer from Analog Devices Ltd. The entire design has been develop using a standard notebook with Windows 10 operating system. The major interest of presenting this design is that in wide range of conditions, the self-made system developed from scratch with elements, price of which does not exceed 15 USD, is capable of generating a frequency spectrum equally significant to a spectrum generated by a full-scale, costly commercial condition monitoring system.

This paper describes implementation of the Generalized Predictive Control (GPC) algorithm on an STM32 microcontroller with the ARM Cortex M7 core. The algorithm is implemented in its analytical (explicit) version which requires computationally simple matrix and vector operations in real time, no on-line optimisation is necessary. As a result, the algorithm may be used for controlling very fast dynamic processes characterised by sampling periods of millisecond order. Results of real experiments are demonstrated for two example processes.

Four rotor aircraft controlled by remote controller has obvious disadvantages which including high cumulative error, and poor portability and low dynamic response and those decrease the user’s sense of substitution and result in poor touch experiences. This paper proposes a set of control strategies and applies them in flight control and mobile phone terminal. Firstly, STM32 is used to solute the attitude of aircraft by DMP based on MPU6050 and communicates with the Smartphone by wireless WIFI communication module based on ESP8266. Secondly, the attitude solution of Smartphone is calculated by JAVA development kit and the adjusted Euler angle will be sent to flight control terminal so as to follow the phone attitude. Simulation and the actual test results show that our proposed strategies have good stability and portability.

This paper describes a system for code auto-generation of Model Predictive Control algorithms for Multiple-Input, Multiple-Output processes. Transcompiler – the main part of the system – generates C code of the algorithm, basing on MATLAB code, which contains definition of both algorithms and its parameters. The resulting code is optimised for microcontrollers in terms of memory and computational power necessary for on-line calculation of the optimal values of manipulated variables. This approach may decrease the development time of prototype controllers and lower their cost. Tests are conducted using STM32 microcontroller for simulated processes and results are demonstrated and described.

Based on the ellipsoid fitting algorithm, this paper realized a fast field error calibration compensation method of three-axis magnetic sensor in STM32 embedded systems. Firstly, we analyzed the source of the error and established the error model. Then, we got the error coefficient by computing the parameter of the ellipsoid. At last, we realized this algorithm in STM32 embedded systems. The experiment results showed that the magnetic sensor can be calibrated and compensated in the embedded directly after this system realized. Thus, it is not necessary to collect data and process data in MATLAB. And, the accuracy compensated by the embedded system has not been reduced more than 3°, meets general commercial requirements.

STM32 is a microcontroller based on CortexTM-M3 core; it plays an important role in the embedded control field. This chapter introduces a low-power humidity and temperature collector with SHT10 humidity and temperature sensors. This chapter introduces and implements the communication time sequence of SHT10. A calibration text proves that the system can measure temperature and humidity correctly. It is demonstrated by experiments that this low-power collector can collect data for 30 days and satisfy the design index; besides, the principle of low power can be used in other embedded control field.