2025.9.2 1. 新增走航任务统计功能（待完成）

feiyu02

2025-09-02 8c6e742562d0c8647e0ee8deff01a3eb176d677b

 src/main/kotlin/com/flightfeather/uav/biz/sourcetrace/model/PollutedSource.kt

@@ -1,9 +1,16 @@
package com.flightfeather.uav.biz.sourcetrace.model

import com.flightfeather.uav.biz.FactorFilter
import com.flightfeather.uav.common.utils.DateUtil
import com.flightfeather.uav.common.utils.MapUtil
import com.flightfeather.uav.domain.entity.SceneInfo
import com.flightfeather.uav.domain.repository.SceneInfoRep
import com.flightfeather.uav.lightshare.bean.AreaVo
import com.flightfeather.uav.lightshare.bean.SceneInfoVo
import com.flightfeather.uav.lightshare.eunm.SceneType
import com.flightfeather.uav.socket.eunm.FactorType
import org.springframework.beans.BeanUtils
import org.springframework.web.context.ContextLoader
import kotlin.math.round

/**
 * 污染来源
@@ -19,32 +26,217 @@
     */

    // 溯源企业
    var sceneList:List<SceneInfo?>? = null
    var sceneList: List<SceneInfoVo>? = null

    // 溯源推理结论
    var conclusion: String? = null

    fun searchScenes(pollutedArea: PollutedArea, pollutedData: PollutedData) {
        ContextLoader.getCurrentWebApplicationContext()?.getBean(SceneInfoRep::class.java)?.run {
            searchScenes(pollutedArea, this, pollutedData)
        }
    }

    /**
     * 查找系统内部溯源范围内的污染企业
     */
    fun searchScenes(pollutedArea: PollutedArea, sceneInfoRep: SceneInfoRep, factor: FactorFilter.SelectedFactor) {
    fun searchScenes(pollutedArea: PollutedArea, sceneInfoRep: SceneInfoRep, pollutedData: PollutedData) {
        // Fixme 2025.5.14: 污染源的坐标是高德地图坐标系（火星坐标系），而走航数据是WGS84坐标系
        // 按照区域检索内部污染源信息
        // 1. 首先按照四至范围从数据库初步筛选污染源，需要先将坐标转换为gcj02（火星坐标系），因为污染源场景信息都为此坐标系
        val polygonTmp = pollutedArea.polygon!!.map {
            MapUtil.gcj02ToWgs84(it)
        }
        val fb = MapUtil.calFourBoundaries(polygonTmp)
        val sceneList = sceneInfoRep.findByCoordinateRange(fb)
        // 2. 再精确判断是否在反向溯源区域多边形内部
        val result = mutableListOf<SceneInfo>()
        sceneList.forEach {
            val point = it!!.longitude.toDouble() to it.latitude.toDouble()
            if (MapUtil.isPointInPolygon(point, polygonTmp)) {
                result.add(it)
        var result = mutableListOf<SceneInfo>()
        // 1. 首先按照四至范围从数据库初步筛选污染源，此处的区域坐标已转换为火星坐标系
        val polygonTmp = pollutedArea.polygon
        this.sceneList = emptyList()

        if (polygonTmp != null) {
            val fb = MapUtil.calFourBoundaries(polygonTmp)
            val sceneList = sceneInfoRep.findByCoordinateRange(fb)
            // 2. 再精确判断是否在反向溯源区域多边形内部
            sceneList.forEach {
                val point = it!!.longitude.toDouble() to it.latitude.toDouble()
                if (MapUtil.isPointInPolygon(point, polygonTmp)) {
                    result.add(it)
                }
            }

            val closePolygonTmp = pollutedArea.closePolygon!!
            val closeFb = MapUtil.calFourBoundaries(closePolygonTmp)
            val closeSceneList = sceneInfoRep.findByCoordinateRange(closeFb)
            closeSceneList.forEach {
                val point = it!!.longitude.toDouble() to it.latitude.toDouble()
                if (MapUtil.isPointInPolygon(point, closePolygonTmp)) {
                    result.add(it)
                }
            }
            // 去重
            result = result.distinctBy { it.guid }.toMutableList()

            // 根据污染因子的量级，计算主要的污染场景类型，筛选结果
            val mainSceneType = calSceneType(pollutedData)
            if (mainSceneType != null) {
//            this.conclusion = mainSceneType.first
                result = result.filter {
                    val r = mainSceneType.second.find { s ->
                        s.value == it.typeId.toInt()
                    }
                    r != null
                }.toMutableList()
            }
            this.sceneList = findClosestStation(sceneInfoRep, result)
        }

        this.sceneList = result
        val txt = summaryTxt(pollutedData, this.sceneList!!)
        this.conclusion = txt
    }

        TODO("按照所选监测因子类型，区分污染源类型")
    /**
     * 计算可能的相关污染场景类型以及推理结论
     */
    @Throws(Exception::class)
    private fun calSceneType(pollutedData: PollutedData): Pair<String, List<SceneType>>? {
        var des: String? = null
        val sceneTypes = mutableListOf<SceneType>()
        pollutedData.statisticMap.entries.forEach { s ->
            val res = when (s.key) {
                // 氮氧化合物，一般由于机动车尾气，同步计算CO
                FactorType.NO2 -> {
                    val coAvg = round(pollutedData.dataList.map { it.co!! }.average()) / 1000
                    "氮氧化合物偏高，CO的量级为${coAvg}mg/m³，一般由于机动车尾气造成，污染源以汽修、加油站为主" to
                            listOf(SceneType.TYPE6, SceneType.TYPE10, SceneType.TYPE17)
                }

                FactorType.CO -> null

                FactorType.H2S -> null

                FactorType.SO2 -> null

                FactorType.O3 -> null
                // a) pm2.5、pm10特别高，两者在各情况下同步展示，pm2.5占pm10的比重变化，比重越高，越有可能是餐饮
                // b) pm10特别高、pm2.5较高，大颗粒扬尘污染，只展示pm10，pm2.5占pm10的比重变化，工地为主
                FactorType.PM25,
                FactorType.PM10,
                    -> {
                    val pm25Avg = round(pollutedData.dataList.map { it.pm25!! }.average() * 10) / 10
                    val pm10Avg = round(pollutedData.dataList.map { it.pm10!! }.average() * 10) / 10
                    // 计算异常数据的pm2.5占pm10比重的均值
                    val percentageAvg = pollutedData.dataList.map {
                        it.pm25!! / it.pm10!!
                    }.average()
                    val str =
                        "PM2.5量级为${pm25Avg}μg/m³，PM10量级为${pm10Avg}μg/m³，PM2.5占PM10的比重为${round(percentageAvg * 100)}%"
                    if (percentageAvg > 0.666) {
                        "${str}，比重较大，污染源以餐饮为主，工地次之" to
                                listOf(
                                    SceneType.TYPE1,
                                    SceneType.TYPE2,
                                    SceneType.TYPE3,
                                    SceneType.TYPE14,
                                    SceneType.TYPE5
                                )
                    } else if (percentageAvg < 0.333) {
                        "${str}，比重较小，属于大颗粒扬尘污染，污染源以工地为主" to
                                listOf(
                                    SceneType.TYPE1,
                                    SceneType.TYPE2,
                                    SceneType.TYPE3,
                                    SceneType.TYPE14,
                                    SceneType.TYPE5
                                )
                    } else {
                        "${str}，污染源以餐饮、工地为主" to
                                listOf(
                                    SceneType.TYPE1,
                                    SceneType.TYPE2,
                                    SceneType.TYPE3,
                                    SceneType.TYPE14,
                                    SceneType.TYPE5
                                )
                    }
                }
                // c) VOC较高，同比计算pm2.5的量级，可能存在同步偏高（汽修、加油站）, 同步计算O3是否有高值
                // d) VOC较高，处于加油站（车辆拥堵情况），CO一般较高, 同步计算O3是否有高值
                FactorType.VOC -> {
                    val pm25Avg = round(pollutedData.dataList.map { it.pm25!! }.average() * 10) / 10
                    val coAvg = round(pollutedData.dataList.map { it.co!! }.average()) / 1000
                    val o3Avg = round(pollutedData.dataList.map { it.o3!! }.average() * 10) / 10
                    "VOC偏高，同时PM2.5量级为${pm25Avg}μg/m³，CO量级为${coAvg}mg/m³，O3量级为${o3Avg}μg/m³，污染源以汽修、加油站为主" to
                            listOf(SceneType.TYPE6, SceneType.TYPE17, SceneType.TYPE12)
                }

                else -> null
            }
            des = res?.first
            res?.second?.let { sceneTypes.addAll(it) }
        }
        return (des ?: "") to sceneTypes
    }

    /**
     * 计算最近的监测站点
     */
    private fun findClosestStation(sceneInfoRep: SceneInfoRep, sceneList: List<SceneInfo>): List<SceneInfoVo> {
        val res1 = sceneInfoRep.findByArea(AreaVo().apply {
            sceneTypeId = SceneType.TYPE19.value.toString()
        })

        val res2 = sceneInfoRep.findByArea(AreaVo().apply {
            sceneTypeId = SceneType.TYPE20.value.toString()
        })
        val res = res1.toMutableList().apply { addAll(res2) }

        return sceneList.map {
            var minLen = -1.0
            var selectedRes: SceneInfo? = null
            res.forEach { r ->
                val dis = MapUtil.getDistance(
                    it.longitude.toDouble(),
                    it.latitude.toDouble(),
                    r!!.longitude.toDouble(),
                    r.latitude.toDouble()
                )
                if (minLen < 0 || dis < minLen) {
                    minLen = dis
                    selectedRes = r
                }
            }
            val vo = SceneInfoVo()
            BeanUtils.copyProperties(it, vo)
            vo.closestStation = selectedRes
            vo.length = minLen

            return@map vo
        }
    }

    private fun summaryTxt(pollutedData: PollutedData, sceneList: List<SceneInfoVo>): String {
//        pollutedData.exception
//        pollutedData.selectedFactor?.main
        val st = DateUtil.instance.getTime(pollutedData.startTime)
        val et = DateUtil.instance.getTime(pollutedData.endTime)
        var txt =
            "在${st}至${et}之间，出现${pollutedData.exception}"
        pollutedData.statisticMap.entries.forEach { s ->
            txt += "，${s.key.des}最低值为${s.value.min}μg/m³，最高值为${s.value.max}μg/m³，均值为${s.value.avg}μg/m³"
        }
        if (sceneList.isEmpty()) {
            txt += ("，可能存在隐藏风险源。")
        } else {
            txt += ("，发现${sceneList.size}个风险源，包含")

            val sizeMap = mutableMapOf<String, Int>()
            sceneList.forEach {
                if (!sizeMap.containsKey(it.type)) {
                    sizeMap[it.type] = 0
                }
                sizeMap[it.type] = sizeMap[it.type]!! + 1
            }
            sizeMap.forEach { (t, u) ->
                txt += ("${u}个${t}，")
            }
            txt = txt.replaceRange(txt.length - 1, txt.length, "。")
        }

        return txt
    }
}