创新背景

垃圾处理包括最初的垃圾分类和之后的消除，两者都需要细化处理保证不二次产生环境有害物。电力工程到目前为止最依赖的还是火力发电，再化石燃料之外，人们逐渐将生产生活产生的垃圾焚烧进行发电，进行废物利用。

创新过程

垃圾处理面临量大类杂的问题，再最初的分类处理上就存在不少难处。2019年的科博会上，有关科技公司展示了利用人工智能进行垃圾分类的便利之处。垃圾分类之后可以转化为资源，公司团队和芬兰企业一样，着重落脚将人工智能的垃圾分拣算法训练，让人工智能能准确、高效地分拣垃圾，包括重型建筑垃圾。

将机器人和人工智能相结合，设置深度视觉识别算法和技术，进行不断训练、学习和迭代，机器人的识别效率再不断训练中越来越高，准确度不断攀升，逐渐熟悉各种垃圾的种类和特点。配合机器人高速的分拣技术，最终实现一体化智能分拣。把机器人6个编组分布再垃圾分拣处理线上，特定识别各自的分拣类型，可促进每年15万吨的垃圾精细分拣。

人工智能进入垃圾分拣领域，大幅度降低了人力资源的耗费和对身体的伤害，提高垃圾处理效率。同时，在垃圾焚烧发电领域，人工智能起到重要作用。

垃圾焚烧发电和化石燃料不同，没有恒定的热值和排除废气，垃圾品类、数量、比重等不同，焚烧发电的效率以及产生的废物也不同。将人工智能引入垃圾焚烧发电，除了以往的数据传输和分析，还对人工操作进行深度模拟。对燃烧过程的各项设备运转提供实时的数值反应和关联匹配，保证不过度耗能，抓紧时机将各项流程连接运转。同时去除不必要的信息，保留操作的关键关联信息。

并且在人工智能系统中设置预留空间设计预测和猜想防护，在极限大小值处装有报警系统，控制发电过程的废弃产生和燃烧温度。同时将燃烧废料，如二氧化硫等有害物质和废弃温度有效保存，帮助进行下一步废物利用，把有害物质转化成能源高效利用。

人工智能进入垃圾处理领域，将大大提高垃圾处理的效率并促进废物循环利用发展，对环境保护和能源再生具有重要意义。

创新关键点

创新在垃圾处理领域使用人工智能，分拣、燃烧一体化进行，促进工作高效绿色运转。

Use artificial intelligence to dispose of garbage

Garbage disposal is faced with a large amount of miscellaneous problems, and there are many difficulties in the initial classification and disposal. At the 2019 Science Expo, relevant technology companies demonstrated the convenience of using artificial intelligence for waste sorting. Garbage can be converted into resources after sorting. Like Finnish companies, the company's team focuses on training artificial intelligence garbage sorting algorithms, so that artificial intelligence can accurately and efficiently sort garbage, including heavy construction waste.
Combining robots with artificial intelligence, setting up deep visual recognition algorithms and technologies, and carrying out continuous training, learning and iteration, the recognition efficiency of robots is getting higher and higher with continuous training, and the accuracy is rising, and gradually become familiar with the types and characteristics of various garbage . With the high-speed sorting technology of robots, integrated intelligent sorting is finally realized. Distributing 6 groups of robots on the garbage sorting and processing line, and identifying their respective sorting types, can promote the fine sorting of 150,000 tons of garbage per year.
Artificial intelligence has entered the field of garbage sorting, greatly reducing the consumption of human resources and physical harm, and improving the efficiency of garbage disposal. At the same time, in the field of waste incineration power generation, artificial intelligence plays an important role.
Waste incineration power generation is different from fossil fuels, there is no constant calorific value and exhaust gas is discharged, the type, quantity and specific gravity of waste are different, the efficiency of incineration power generation and the waste generated are also different. The introduction of artificial intelligence into waste incineration power generation, in addition to the previous data transmission and analysis, also conducts in-depth simulation of manual operations. Provide real-time numerical response and correlation matching for the operation of various equipment in the combustion process to ensure that there is no excessive energy consumption, and seize the opportunity to connect and operate various processes. At the same time, unnecessary information is removed, and the key related information of the operation is preserved.
In addition, reserved space is set up in the artificial intelligence system to design prediction and guess protection, and an alarm system is installed at the limit value to control the waste generation and combustion temperature of the power generation process. At the same time, the combustion waste, such as sulfur dioxide and other harmful substances and the waste temperature are effectively preserved to help the next step of waste utilization, and the harmful substances can be converted into energy for efficient use.
The entry of artificial intelligence into the field of waste treatment will greatly improve the efficiency of waste treatment and promote the development of waste recycling, which is of great significance to environmental protection and energy regeneration.