At present, the Internet of Things industry is booming, combining objects and networks, forming a world of connected objects is bound to be the development direction of society. The OneNET platform is currently the largest cloud platform for IoT devices in China, and is used for various cross-platform IoT applications. Provides easy cloud access, storage, computing and presentation functions. This project is based on the OneNET platform and provides data logging and anti-theft alarm functions through illumination sensors and human body infrared sensors.
System Overview
1. System structure
The sensor consists of an integrated illumination sensor and an infrared sensor. It is responsible for collecting light intensity and infrared sensing data, and uploading the data to the OneNET platform via the wifi module.
As the IoT device cloud platform, the OneNET platform provides easy device cloud access, storage, computing and display functions. In this project, it is responsible for storing data and data presentation from the sensor side.
The data processing terminal is written in Java language and is responsible for accessing the OneNET platform, obtaining data information stored on the OneNET platform, processing the data, and uploading the processing results to the OneNET platform.
2. System function
Collect and record light intensity and infrared sensing data and provide data display capabilities.
The collected data is analyzed. When the light intensity is low (evening), someone is detected and the system activates the alarm function.
Implementation
1. Sensor end:
Hardware module selection: OneNET Unicorn development board V1.2, infrared sensor module, light sensor GY-30
Hardware processing flow:
2.OneNET platform:
interface design:
As shown in the figure, an application is built on the platform to provide recording and display of light intensity and infrared sensing information. When the light intensity is less than 20, the sun icon will become the moon, and if this is detected, if someone is detected When entering, an alarm will be given and the alarm light will continue to flash.
Data flow definition:
The display of data and the transformation of images need to be implemented by defining different data streams. This project defines the following data streams:
1. Light intensity data stream: The light intensity is recorded, and the latest data point indicates the current light intensity.
2. Light picture data stream: The sun and moon pictures are switched by the value of the latest data point 0, 1. The data points are processed and processed by the data processing end to upload the processing result.
3. Infrared recording data stream: record the data information of infrared sensing.
4. Alarm picture data stream: The alarm picture is switched by the value of the data point, and the data point is uploaded by the data processing end.
5, text prompt data stream: according to different situations, the corresponding text prompts are displayed, and the text content is uploaded by the data processing end.
3. Data processing end:
The data processing end is responsible for obtaining the data of the OneNET platform and performing analysis and processing, and returns the processing result. The basic process is as shown in the following figure:
Main function:
HttpConnect class: Connect to the OneNET platform via httpUrlconnecTIon, write GET, POST, PUT and DELET requests to provide an interface for data reception and upload.
JsonBean class: Since the data obtained from the platform is in json format, the JsonBean class is written, and the json format data is converted into a java object by the Gson method.
FuncTIon class: Provides functional interfaces, including device addition, query, data point addition, and query.
Warn class: By analyzing the acquired data, the corresponding processing result is obtained, and the function of FuncTIon is called to implement the corresponding function.
Project value
The project is based on the OneNET platform, which monitors and uploads data through sensors, and the data processing end obtains data analysis and processing. The burglar alarm system is successfully implemented. The difficulty of the project lies in the interface definition, data acquisition and upload of the external sensor of the Unicorn development board. The data processing end accesses the platform to obtain data and parsing the code. Through the development of this project, the process of actual application is generated, and the characteristics and use of the OneNET platform are further understood. The developed product has practical significance and can be extended to a large area alarm alarm integrated system.
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