From 94fee0b511279679b43e210878d3d36e5a14384b Mon Sep 17 00:00:00 2001
From: feiyu02 <risaku@163.com>
Date: 星期二, 30 九月 2025 09:14:10 +0800
Subject: [PATCH] 2025.9.30 1. 新增走航任务统计功能
---
src/main/kotlin/com/flightfeather/uav/domain/entity/BaseRealTimeData.kt | 289 +++++++++++++++++++++++++++++++++++++++++++++++++++++++++
1 files changed, 288 insertions(+), 1 deletions(-)
diff --git a/src/main/kotlin/com/flightfeather/uav/domain/entity/BaseRealTimeData.kt b/src/main/kotlin/com/flightfeather/uav/domain/entity/BaseRealTimeData.kt
index a94c014..53989b5 100644
--- a/src/main/kotlin/com/flightfeather/uav/domain/entity/BaseRealTimeData.kt
+++ b/src/main/kotlin/com/flightfeather/uav/domain/entity/BaseRealTimeData.kt
@@ -1,19 +1,31 @@
package com.flightfeather.uav.domain.entity
+import com.flightfeather.uav.biz.dataprocess.AvgPair
import com.flightfeather.uav.common.utils.DateUtil
import com.flightfeather.uav.lightshare.bean.DataVo
+import com.flightfeather.uav.lightshare.bean.FactorStatistics
import com.flightfeather.uav.socket.bean.AirData
import com.flightfeather.uav.socket.eunm.FactorType
+import java.io.Serializable
import java.math.BigDecimal
+import java.time.LocalDateTime
+import java.time.ZoneId
import java.util.*
import javax.persistence.Column
+import javax.persistence.GeneratedValue
+import javax.persistence.GenerationType
import javax.persistence.Id
+import kotlin.math.atan
+import kotlin.math.cos
+import kotlin.math.round
+import kotlin.math.sin
/**
* 瀹炴椂鐩戞祴鏁版嵁鍩虹被
*/
-open class BaseRealTimeData {
+open class BaseRealTimeData : Serializable {
@Id
+ @GeneratedValue(strategy = GenerationType.IDENTITY)
var id: Int? = null
@Column(name = "device_code")
@@ -62,6 +74,9 @@
@Column(name = "NOI")
var noi: Float? = null
+ @Column(name = "NO")
+ var no: Float? = null
+
var velocity: Float? = null
@Column(name = "wind_speed")
@@ -101,6 +116,278 @@
add(AirData().apply { setData(FactorType.WIND_SPEED, windSpeed) })
add(AirData().apply { setData(FactorType.WIND_DIRECTION, windDirection) })
add(AirData().apply { setData(FactorType.HEIGHT, height) })
+ add(AirData().apply { setData(FactorType.NO, no) })
}
}
+
+ fun getByFactorType(type: FactorType?): Float? {
+ return when (type) {
+ FactorType.NO2 -> no2
+ FactorType.CO -> co
+ FactorType.H2S -> h2s
+ FactorType.SO2 -> so2
+ FactorType.O3 -> o3
+ FactorType.PM25 -> pm25
+ FactorType.PM10 -> pm10
+ FactorType.TEMPERATURE -> temperature
+ FactorType.HUMIDITY -> humidity
+ FactorType.VOC -> voc
+ FactorType.NOI -> noi
+ FactorType.LNG -> longitude?.toFloat()
+ FactorType.LAT -> latitude?.toFloat()
+ FactorType.VELOCITY -> velocity
+// FactorType.TIME -> dataTime?.time?.toFloat()
+ FactorType.WIND_SPEED -> windSpeed
+ FactorType.WIND_DIRECTION -> windDirection
+ FactorType.HEIGHT -> height
+ FactorType.NO -> no
+ else -> null
+ }
+ }
+
+}
+
+fun List<BaseRealTimeData>.avg(onEach: (BaseRealTimeData) -> Unit = { }): BaseRealTimeData {
+ if (isEmpty()) {
+ return BaseRealTimeData()
+ }
+ //椋庡悜閲囩敤鍗曚綅鐭㈤噺娉曟眰鍙栧潎鍊�
+ var u = .0//涓滆タ鏂逛綅鍒嗛噺鎬诲拰
+ var v = .0//鍗楀寳鏂逛綅鍒嗛噺鎬诲拰
+ var c = 0//椋庡悜鏁版嵁璁℃暟
+
+ //闄ら鍚戝鐨勫叾浠栧洜瀛愰噰鐢ㄧ畻鏈钩鍧囨硶姹傚彇鍧囧��
+ val tmpList = mutableListOf<AvgPair>()
+ repeat(18) {
+ tmpList.add(AvgPair(0f, 0))
+ }
+
+ forEach {
+ onEach(it)
+ //椋庡悜
+ it.windDirection?.let { w ->
+ val r = Math.toRadians(w.toDouble())
+ u += sin(r)
+ v += cos(r)
+ c++
+ }
+ //鍏朵綑鍥犲瓙
+ tmpList[0].apply {
+ it.latitude?.let {
+ t += it.toFloat()
+ this.c++
+ }
+ }
+ tmpList[1].apply {
+ it.longitude?.let {
+ t += it.toFloat()
+ this.c++
+ }
+ }
+ tmpList[2].apply {
+ it.altitude?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[3].apply {
+ it.no2?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[4].apply {
+ it.co?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[5].apply {
+ it.h2s?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[6].apply {
+ it.so2?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[7].apply {
+ it.o3?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[8].apply {
+ it.pm25?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[9].apply {
+ it.pm10?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[10].apply {
+ it.temperature?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[11].apply {
+ it.humidity?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[12].apply {
+ it.voc?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[13].apply {
+ it.noi?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[14].apply {
+ it.velocity?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[15].apply {
+ it.windSpeed?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[16].apply {
+ it.height?.let {
+ t += it
+ this.c++
+ }
+ }
+ tmpList[17].apply {
+ it.no?.let {
+ t += it
+ this.c++
+ }
+ }
+ }
+
+ return RealTimeDataGridMin().apply {
+ val time = LocalDateTime
+ .ofInstant(get(0).dataTime?.toInstant() ?: Date().toInstant(), ZoneId.systemDefault())
+ .withSecond(0)
+ deviceCode = get(0).deviceCode
+ dataTime = Date.from(time.atZone(ZoneId.systemDefault()).toInstant())
+ createTime = dataTime
+ latitude = tmpList[0].avg().toBigDecimal()
+ longitude = tmpList[1].avg().toBigDecimal()
+ altitude = tmpList[2].avg()
+ no2 = tmpList[3].avg()
+ co = tmpList[4].avg()
+ h2s = tmpList[5].avg()
+ so2 = tmpList[6].avg()
+ o3 = tmpList[7].avg()
+ pm25 = tmpList[8].avg()
+ pm10 = tmpList[9].avg()
+ temperature = tmpList[10].avg()
+ humidity = tmpList[11].avg()
+ voc = tmpList[12].avg()
+ noi = tmpList[13].avg()
+ velocity = tmpList[14].avg()
+ windSpeed = tmpList[15].avg()
+ height = tmpList[16].avg()
+ no = tmpList[17].avg()
+
+ if (c != 0) {
+ val avgU = u / c
+ val avgV = v / c
+ var a = atan(avgU / avgV)
+ a = Math.toDegrees(a)
+ /**
+ * avgU>0;avgV>0: 鐪熷疄瑙掑害澶勪簬绗竴璞￠檺锛屼慨姝ｅ�间负+0掳
+ * avgU>0;avgV<0: 鐪熷疄瑙掑害澶勪簬绗簩璞￠檺锛屼慨姝ｅ�间负+180掳
+ * avgU<0;avgV<0: 鐪熷疄瑙掑害澶勪簬绗笁璞￠檺锛屼慨姝ｅ�间负+180掳
+ * avgU<0;avgV>0: 鐪熷疄瑙掑害澶勪簬绗洓璞￠檺锛屼慨姝ｅ�间负+360掳
+ */
+ a += if (avgV > 0) {
+ if (avgU > 0) 0 else 360
+ } else {
+ 180
+ }
+ windDirection = round(a.toFloat())
+ }
+ }
+}
+
+/**
+ * 璁＄畻瀹炴椂鐩戞祴鏁版嵁鍒楄〃鐨勭粺璁′俊鎭�
+ * 涓烘瘡绉嶇幆澧冨洜瀛愯绠楁渶灏忓�笺�佹渶澶у�煎拰骞冲潎鍊�
+ *
+ * @return 鍖呭惈鍚勭幆澧冨洜瀛愮粺璁′俊鎭殑FactorStatistics鍒楄〃
+ * 姣忎釜FactorStatistics瀵硅薄鍖呭惈鍥犲瓙绫诲瀷銆佹渶灏忓�笺�佹渶澶у�煎拰骞冲潎鍊�
+ */
+fun List<BaseRealTimeData>.calDataStatistics(): List<FactorStatistics> {
+
+ // 鍒濆鍖栧悇鐜鍥犲瓙鐨勭粺璁″璞″垪琛�
+ val statistics = mutableListOf<FactorStatistics>()
+ listOf(
+ FactorType.NO2,
+ FactorType.CO,
+ FactorType.H2S,
+ FactorType.SO2,
+ FactorType.O3,
+ FactorType.PM25,
+ FactorType.PM10,
+ FactorType.VOC,
+ FactorType.NOI,
+ FactorType.VELOCITY,
+ FactorType.WIND_SPEED,
+ FactorType.HEIGHT,
+ FactorType.NO
+ ).forEach { statistics.add(FactorStatistics(it)) }
+
+ // 璁＄畻骞冲潎鍊煎苟鍚屾椂鏇存柊鍚勫洜瀛愮殑鏈�灏忓�煎拰鏈�澶у��
+ val avgData = avg { item ->
+ // 鏇存柊姣忎釜鍥犲瓙鐨勬渶灏忓拰鏈�澶у��
+ statistics[0].updateMinAndMaxValue(item.no2)
+ statistics[1].updateMinAndMaxValue(item.co)
+ statistics[2].updateMinAndMaxValue(item.h2s)
+ statistics[3].updateMinAndMaxValue(item.so2)
+ statistics[4].updateMinAndMaxValue(item.o3)
+ statistics[5].updateMinAndMaxValue(item.pm25)
+ statistics[6].updateMinAndMaxValue(item.pm10)
+ statistics[7].updateMinAndMaxValue(item.voc)
+ statistics[8].updateMinAndMaxValue(item.noi)
+ statistics[9].updateMinAndMaxValue(item.velocity)
+ statistics[10].updateMinAndMaxValue(item.windSpeed)
+ statistics[11].updateMinAndMaxValue(item.height)
+ statistics[12].updateMinAndMaxValue(item.no)
+ }
+
+ // 灏嗚绠楀緱鍒扮殑骞冲潎鍊艰缃埌瀵瑰簲鐨勭粺璁″璞′腑
+ statistics[0].avgValue = avgData.no2 ?: 0f
+ statistics[1].avgValue = avgData.co ?: 0f
+ statistics[2].avgValue = avgData.h2s ?: 0f
+ statistics[3].avgValue = avgData.so2 ?: 0f
+ statistics[4].avgValue = avgData.o3 ?: 0f
+ statistics[5].avgValue = avgData.pm25 ?: 0f
+ statistics[6].avgValue = avgData.pm10 ?: 0f
+ statistics[7].avgValue = avgData.voc ?: 0f
+ statistics[8].avgValue = avgData.noi ?: 0f
+ statistics[9].avgValue = avgData.velocity ?: 0f
+ statistics[10].avgValue = avgData.windSpeed ?: 0f
+ statistics[11].avgValue = avgData.height ?: 0f
+ statistics[12].avgValue = avgData.no ?: 0f
+
+ return statistics
}
\ No newline at end of file
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