How to use Java to write a smart home control system based on speech recognition

With the rapid development of artificial intelligence technology, smart home has become one of the hottest topics nowadays. How to implement a smart home control system has become the focus of many developers. This article will introduce in detail how to use Java language to write a smart home control system based on speech recognition.

1. Requirements Analysis

The main functions of the smart home control system are: controlling the switches, temperature, humidity and other parameters of various smart devices in the home. At the same time, the system needs to support voice-based operations, such as voice wake-up, voice control, etc.

2. Technology Selection

This system is developed using Java language. The main technologies include:

1. Speech recognition technology: the speech recognition API of Baidu AI open platform.

2. Smart device control technology: Use MQTT protocol to interact with specific smart devices.

3. Front-end display technology: Use Spring Boot as the basic framework and Vue.js as the front-end framework.

3. System Design

The entire smart home system can be divided into three main parts: speech recognition, MQTT protocol communication, and front-end display. They are introduced below.

Speech recognition part

Using the speech recognition API provided by Baidu AI open platform, speech input can be realized and speech can be converted into text format. Next we need to parse the received speech and perform corresponding operations based on the parsing results.

MQTT protocol communication

MQTT is a lightweight, flexible, and simple machine-to-machine (M2M) communication protocol suitable for communication in the Internet of Things. In smart home systems, the MQTT protocol can be used as the communication protocol between smart devices and systems.

Front-end display

The front-end of the system uses the Vue.js framework, which can display the recognized speech and corresponding operation results. At the same time, the system supports the voice wake-up function. Just say the keyword "little assistant" and the system can enter the recognition state.

4. System Implementation

Baidu Speech Recognition API

The Baidu AI open platform provides a REST-based API interface, which can be directly called for speech recognition. The API is used as follows:

public String recognize(InputStream ins, String format, int rate, String token) throws Exception {
        String url = "https://vop.baidu.com/server_api";
        url += "?cuid=" + "test";
        url += "&token=" + token;
        url += "&dev_pid=" + "1536";
        url += "&rate=" + rate;
        url += "&channel=" + "1";
        String result = "";
        byte[] data = readInputStream(ins);
        String base64Data = Base64Utils.encodeToString(data);
        try {
            Map<String, Object> paramMap = new HashMap<>();
            paramMap.put("format", format);
            paramMap.put("speech", base64Data);
            paramMap.put("len", data.length);
            paramMap.put("cuid", "test");
            paramMap.put("token", token);
            paramMap.put("dev_pid", "1536");
            paramMap.put("rate", rate);
            paramMap.put("channel", 1);
            HttpHeaders headers = new HttpHeaders();
            MediaType type = MediaType.parseMediaType("application/json;charset=UTF-8");
            headers.setContentType(type);
            HttpEntity<Map<String, Object>> request = new HttpEntity<>(paramMap, headers);
            ResponseEntity<String> responseEntity = restTemplate.postForEntity(url, request, String.class);
            if (responseEntity.getStatusCode() == HttpStatus.OK) {
                result = responseEntity.getBody();
            }
        } catch (Exception e) {
            e.printStackTrace();
            result = "error:" + e.getMessage();
        }
        return result;
}

MQTT protocol communication

Before using MQTT protocol communication, you need to understand the relevant knowledge of MQTT, including MQTT protocol, MQTT client, etc. We use the Paho MQTT client library to implement communication. For specific implementation, please refer to the following code:

MqttClient mqttClient = new MqttClient(brokerUrl, clientId, persistence);
mqttClient.setCallback(new MqttCallback() {

    public void messageArrived(String topic, MqttMessage message) throws Exception {
        System.out.println(Thread.currentThread().getName());
        System.out.println("收到消息主题 : " + topic);
        System.out.println("收到消息Qos : " + message.getQos());
        System.out.println("收到消息内容 : " + new String(message.getPayload()));
    }

    public void deliveryComplete(IMqttDeliveryToken token) {
        
    }

    public void connectionLost(Throwable cause) {
        System.out.println("连接断开，可以做重连");

    }
});
MqttConnectOptions connOpts = new MqttConnectOptions();
connOpts.setCleanSession(true);
connOpts.setUserName(userName);
connOpts.setPassword(password.toCharArray());
connOpts.setConnectionTimeout(10);
connOpts.setKeepAliveInterval(20);
mqttClient.connect(connOpts);

Front-end display

Using the Vue.js framework, you can quickly build a front-end display. For specific implementation, please refer to the following code. ：

import Vue from 'vue'
import App from './App.vue'
import ElementUI from 'element-ui';
import 'element-ui/lib/theme-chalk/index.css';

Vue.config.productionTip = false
Vue.use(ElementUI)

new Vue({
  render: h => h(App),
}).$mount('#app')

5. System testing

After completing the system design and implementation, testing needs to be performed. The test is mainly conducted from the following two aspects:

1. Speech recognition test: By reading the specified speech content, test whether the system can correctly recognize the speech content and output the recognition result.

2. Control device testing: By controlling different types of smart devices, test whether the system can correctly control the status of the device.

6. Summary

This article introduces in detail how to use Java language to write a smart home control system based on speech recognition. During the implementation process, it is necessary to apply Baidu AI open platform's speech recognition API, MQTT protocol communication, Vue.js and other technologies. At the same time, during the system testing process, it is necessary to focus on testing the speech recognition function and device control function.

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