数据集成-电表关联区域；运行分析客流监控和空气质量优化

package.json

@@ -31,6 +31,7 @@
     "tencentcloud-sdk-nodejs": "^4.0.562",
     "winston": "^3.17.0",
     "ws": "^5.2.2",
+    "xlsx": "^0.18.5",
     "xml2js": "^0.4.23",
     "xmlrpc": "^1.3.2"
   },

src/biz/dataIntegration.ts

@@ -7,6 +7,8 @@ import {
 } from "./feiyiClient";
 import { mysqlModelMap } from "../model/sqlModelBind";
 import moment from "moment";
+import XLSX from "xlsx";
+import path from "path";
 
 // ==================== 工具函数 ====================
 
@@ -17,6 +19,42 @@ function getTodayDateStr(): string {
     return moment().format('YYYYMMDD');
 }
 
+/**
+ * 从内机四段地址（如 "2-1-0-1"）提取外机地址（"2-1-0"）
+ */
+function getOuterAddress(indoorUnitAddressFull: string): string | null {
+    if (!indoorUnitAddressFull) return null;
+    const parts = indoorUnitAddressFull.split('-');
+    if (parts.length >= 3) {
+        return parts.slice(0, 3).join('-');
+    }
+    return null;
+}
+
+/**
+ * 从 Excel 文件读取电表设备编号 → 外机地址 的映射表
+ */
+function loadMeterOuterAddrMap(): Map<string, string> {
+    const map = new Map<string, string>();
+    try {
+        const filePath = path.resolve(__dirname, '../../res/电表对应区域.xlsx');
+        const workbook = XLSX.readFile(filePath);
+        const sheet = workbook.Sheets[workbook.SheetNames[0]];
+        const rows: any[] = XLSX.utils.sheet_to_json(sheet);
+        for (const row of rows) {
+            const meterCode = row['电表设备编号'];
+            const outerAddr = row['空调外机地址'];
+            if (meterCode && outerAddr) {
+                map.set(String(meterCode), String(outerAddr));
+            }
+        }
+        console.log(`[工具] 电表对应区域.xlsx 读取完成，共 ${map.size} 条映射`);
+    } catch (err) {
+        console.error('[工具] 读取电表对应区域.xlsx 失败:', err);
+    }
+    return map;
+}
+
 // ==================== 分页拉取辅助函数 ====================
 
 /**
@@ -150,11 +188,137 @@ export async function region() {
         }
 
         console.log(`[区域集成] 完成，新增 ${insertCount} 条，跳过 ${skipCount} 条已存在`);
+
+        // 2. 一次性查询所有 region，后续两步共用内存数据，避免 DB 读写时序问题
+        const allRegions = await regionModel.findAll({ raw: true }) as any[];
+
+        // 3. 同步空调内机 → 反写 region.address
+        const updatedRegions = await syncRegionAddressByAcDevices(regionModel, allRegions);
+
+        // 4. 同步电表设备 region_key（复用上一步已更新 address 的内存数据）
+        await syncMeterDeviceRegionKey(updatedRegions);
+
     } catch (err) {
         console.error('[区域集成] 执行异常:', err);
     }
 }
 
+// ==================== 区域-设备关联同步 ====================
+
+/**
+ * 通过空调内机信息反写 region 表的 address 字段（外机地址）
+ * 逻辑：拉取所有空调内机 → 通过 roomId 匹配 region → 用内机地址前三位反写 region.address
+ */
+async function syncRegionAddressByAcDevices(regionModel: any, allRegions: any[]) {
+    console.log('[同步region.address] 开始...');
+    try {
+        // 拉取所有空调内机
+        const rows = await fetchAllPages((page, limit) => getIndoorUnitList({ page, limit }));
+        console.log(`[同步region.address] 共获取 ${rows.length} 条空调内机`);
+
+        // 构建 roomId → region 映射（使用外部传入的 allRegions）
+        const roomIdToRegion = new Map<string, any>();
+        for (const r of allRegions) {
+            if (r.room_id) {
+                roomIdToRegion.set(r.room_id, r);
+            }
+        }
+
+        let updateCount = 0;
+        for (const item of rows) {
+            if (!item.roomId || !item.indoorUnitAddressFull) continue;
+
+            const region = roomIdToRegion.get(item.roomId);
+            if (!region) continue;
+
+            // 用内机四段地址前三位作为外机地址
+            const outerAddr = getOuterAddress(item.indoorUnitAddressFull);
+            if (!outerAddr) continue;
+
+            // address 为空或值不同时才更新
+            if (region.address === outerAddr) continue;
+
+            await regionModel.update(
+                { address: outerAddr },
+                { where: { id: region.id } },
+            );
+            // 同步更新内存中的值，后续 syncMeterDeviceRegionKey 可直接使用
+            region.address = outerAddr;
+            updateCount++;
+        }
+        console.log(`[同步region.address] 完成，更新 ${updateCount} 条`);
+        return allRegions; // 返回已更新 address 的内存数据
+    } catch (err) {
+        console.error('[同步region.address] 执行异常:', err);
+        return allRegions; // 异常时仍返回原始数据，不阻塞后续流程
+    }
+}
+
+/**
+ * 通过 Excel 映射 + region.address 同步电表设备的 region_key
+ * 逻辑：Excel(电表设备编号→外机地址) → region.address → region.id → 更新 device.region_key
+ */
+async function syncMeterDeviceRegionKey(allRegions: any[]) {
+    console.log('[同步电表region_key] 开始...');
+    try {
+        const deviceModel = mysqlModelMap['device'];
+        if (!deviceModel) {
+            console.error('[同步电表region_key] device 表模型未初始化，跳过');
+            return;
+        }
+
+        // 1. 读取 Excel 映射：电表设备编号 → 外机地址
+        const meterOuterMap = loadMeterOuterAddrMap();
+        if (meterOuterMap.size === 0) {
+            console.warn('[同步电表region_key] Excel 映射为空，跳过');
+            return;
+        }
+
+        // 2. 使用外部传入的 allRegions 构建 address → regionId 映射（复用已更新 address 的内存数据）
+        const addrToRegionId = new Map<string, number>();
+        for (const r of allRegions) {
+            if (r.address) {
+                addrToRegionId.set(r.address, r.id);
+            }
+        }
+        console.log(`[同步电表region_key] region.address 映射共 ${addrToRegionId.size} 条`);
+
+        // 3. 查询所有电表设备
+        const meterDevices = await deviceModel.findAll({
+            where: { device_type: '电能监测' },
+            raw: true,
+        });
+        console.log(`[同步电表region_key] 共 ${meterDevices.length} 个电表设备`);
+
+        // 4. 逐一匹配更新
+        let updateCount = 0;
+        let missCount = 0;
+        for (const device of meterDevices as any[]) {
+            const outerAddr = meterOuterMap.get(device.device_id);
+            if (!outerAddr) {
+                missCount++;
+                continue;
+            }
+            const regionId = addrToRegionId.get(outerAddr);
+            if (!regionId) {
+                missCount++;
+                continue;
+            }
+            // region_key 已正确则跳过
+            if (device.region_key === regionId) continue;
+
+            await deviceModel.update(
+                { region_key: regionId },
+                { where: { id: device.id } },
+            );
+            updateCount++;
+        }
+        console.log(`[同步电表region_key] 完成，更新 ${updateCount} 条，未匹配 ${missCount} 条`);
+    } catch (err) {
+        console.error('[同步电表region_key] 执行异常:', err);
+    }
+}
+
 // ==================== 设备集成 ====================
 
 /** 空调控制参数模板（按设备数据结构.md） */

src/biz/running.ts

@@ -128,13 +128,17 @@ export async function getRunAnalysis(regionGroup: string, regionType: string) {
     let airQualityDevices = await selectDataListByParam(TABLENAME.设备表, airParams, ["device_id"]);
     let airDeviceIds = airQualityDevices.data.map(d => d.device_id);
     let qualityIndex = 300;
+
+    // 今日环境质量
+    let todayEnvironmental = '优秀';
+
+    let currentCo2 = 0; // 当前二氧化氮
     let co2Trend = [];
-    let currentCo2 = '0ppm';
-    let currentTemperature = '0℃';
+    let currentTemperature = '0℃'; // 当前温度
     let temperatureTrend = [];
-    let currentHumidity = '0%';
+    let currentHumidity = '0%'; // 当前湿度
     let humidityTrend = [];
-    let currentPm25 = '0μg/m³';
+    let currentPm25 = 0; // 当前PM2.5
     let pm25Trend = [];
     let co2TrendDetail = [];
 
@@ -149,8 +153,8 @@ export async function getRunAnalysis(regionGroup: string, regionType: string) {
             let airData = latestAir.data[0].data;
             currentTemperature = `${airData.temperature ?? 0}℃`;
             currentHumidity = `${airData.humidity ?? 0}%`;
-            currentPm25 = `${airData.pm25 ?? 0}μg/m³`;
-            currentCo2 = `${airData.co2 ?? 0}ppm`;
+            currentPm25 = airData.pm25;
+            currentCo2 = airData.co2 ?? 0;
             qualityIndex = 500 - (airData.pm25 ?? 0);
         }
         // 过去24小时趋势
@@ -179,12 +183,27 @@ export async function getRunAnalysis(regionGroup: string, regionType: string) {
             co2Trend.push({ time: `${i}时`, value: co2Val.toString() });
         }
     }
+
+    // 计算今日环境质量
+    if (currentCo2 && currentPm25) {
+        // 优秀：CO2< 800ppm; PM2.5≤35; 甲醛≤0.055
+        todayEnvironmental = currentCo2<800 && currentPm25<=35 ? '优秀':
+        // 优秀：CO2< 1000ppm; PM2.5≤45; TVOC≤0.4
+        currentCo2<1000 && currentPm25<=45 ? '优秀':
+        // 良好：CO2≤ 1000ppm; PM2.5≤50; 甲醛≤0.08
+        currentCo2<=1000 && currentPm25<=50 ? '良好':
+        // 一般：CO2：1000~1500; PM2.5：50~75
+        currentCo2>1000 && currentCo2<1500 && currentPm25>50 && currentPm25<75 ? '一般': '差'
+    }
+
+
     // 4.2. 环境监测趋势图数据
     resultAny.environmentalTrend = {
+        todayEnvironmental: todayEnvironmental,
         currentTemperature: currentTemperature,
         currentHumidity: currentHumidity,
-        currentPm25: currentPm25,
-        currentCo2: currentCo2,
+        currentPm25: currentPm25+'μg/m³',
+        currentCo2: currentCo2+'ppm',
         temperatureTrend: temperatureTrend,
         humidityTrend: humidityTrend,
         pm25Trend: pm25Trend,
@@ -234,10 +253,10 @@ export async function getRunAnalysis(regionGroup: string, regionType: string) {
     let regionInfos: any = [];
     if (regionKeys.length === 0) {
         // 6.1.1 若没有选择区域，则查询区域表获取所有区域类型
-        regionInfos = await selectDataListByParam(TABLENAME.区域表, {}, ["id", "name", "type"]);
+        regionInfos = await selectDataListByParam(TABLENAME.区域表, {}, ["id", "room_id", "name", "type", "groups"]);
     } else {
         // 6.1.2 若选择了区域，则查询选择的区域
-        regionInfos = await selectDataListByParam(TABLENAME.区域表, { id: { "%in%": regionKeys } }, ["id", "name", "type"]);
+        regionInfos = await selectDataListByParam(TABLENAME.区域表, { id: { "%in%": regionKeys } }, ["id", "room_id", "name", "type", "groups"]);
     }
     
     // 6.2 循环区域查询客流传感器设备，获取过去24小时每个区域的客流量
@@ -246,36 +265,40 @@ export async function getRunAnalysis(regionGroup: string, regionType: string) {
     let regionCustomerMap = new Map(); // {regionName: customerNum}
     let regionCustomerTable = []; // [{regionName: A馆, customerNum: 5000, saturation: '80%'}]
     for (let regionInfo of regionInfos.data) {
-        let customerDevices = await selectDataListByParam(TABLENAME.设备表, { 
-            device_type: "客流传感器", region_key: regionInfo.id 
+        // 区分楼栋与楼层
+        let regionName = regionKeys.length === 0 ? regionInfo.groups : regionInfo.type;
+        // 如果是按区域类型统计，则最大承载量取该类型下所有区域的总和；如果是按区域名称统计，则取该区域的最大承载量
+        let maxCapacity = regionKeys.length === 0 ? regionMaxCustomerMap.get(regionName) : regionInfo.max_capacity;
+        regionMaxCustomerMap.set(regionName, maxCapacity); // 区域最大承载量
+        // 初始化客流量
+        let totalNum = regionCustomerMap.get(regionName) ? regionCustomerMap.get(regionName) : 0;
+
+        let customerDevices = await selectDataListByParam(TABLENAME.设备表, {
+            device_type: "客流传感器", region_key: regionInfo.id
         }, ["device_type", "device_id"]);
         let customerDeviceIds = customerDevices.data.map((d: any) => d.device_id);
         // 获取今日的客流量数据
-        if (customerDeviceIds) {
+        if (customerDeviceIds && customerDeviceIds.length > 0) {
             let customerDeviceDatas = await selectDataListByParam(TABLENAME.设备数据表, {
                 device_id: { "%in%": customerDeviceIds },
                 device_time: { "%gte%": formatLocalTime(todayStart), "%lte%": formatLocalTime(todayEnd) },
                 "%orderAsc%": "device_time"
             }, ["device_id", "data", "device_time"]);
-            
+
             // 统计区域类型的客流量
             for (let rec of customerDeviceDatas.data) {
                 let data = rec.data;
                 if (data.presence === '进') {
                     totalRegionCustomerNum += 1;
-                    // 区分楼栋与楼层
-                    let regionName = regionKeys.length === 0 ? regionInfo.type : regionInfo.name;
                     if (!regionCustomerMap.has(regionName)) {
                         regionCustomerMap.set(regionName, 1);
-                        // 如果是按区域类型统计，则最大承载量取该类型下所有区域的总和；如果是按区域名称统计，则取该区域的最大承载量
-                        let maxCapacity = regionKeys.length === 0 ? regionMaxCustomerMap.get(regionName) : regionInfo.max_capacity;
-                        regionMaxCustomerMap.set(regionName, maxCapacity); // 区域最大承载量
                     } else {
-                        let totalNum = regionCustomerMap.get(regionName);
                         regionCustomerMap.set(regionName, totalNum + 1);
-                    }   
+                    }
                 }
             }
+        } else {
+            regionCustomerMap.set(regionName, totalNum);
         }
     }
     // 计算每个区域的饱和度（客流量/区域最大承载量），并转换成表格

src/config/mysqlTableConfig.ts

@@ -257,6 +257,10 @@ export const TablesConfig = [
                 defaultValue: 0,
                 comment: '排序序号'
             },
+            address: {
+                type: DataTypes.STRING(100),
+                comment: '外机地址'
+            },
             created_at: {
                 type: DataTypes.DATE,
                 allowNull: false,