上海地区居家多测点温度时序监测数据

本数据集为“上海地区居家多测点温度时序监测数据”，记录了上海典型住宅卧室内的五个不同位置在同一时间序列下的实时温度变化。数据覆盖从2025年12月5日8:18:58至2026年1月29日1:13:12的连续监测时段，共计76326条记录，以秒级频率采集，形成高时序分辨率的温度场观测序列。
数据以表格形式组织，共包含7个字段：
1. ID（序号）：每条记录的唯一整数标识，从1开始递增。
2. time（时间戳）：采集时刻，格式为“YYYY-MM-DD HH:MM:SS”，精确到秒。
3. t0（测点0温度）：单位为摄氏度（℃），浮点型，精度为0.01℃。
4. t1（测点1温度）：同上。
5. t2（测点2温度）：同上。
6. t3（测点3温度）：同上。
7. t4（测点4温度）：同上。
所有温度数据均为实测值，反映室内不同空间位置（如近窗、近门、居中等）在自然及人工温控作用下的动态变化。数据结构清晰、字段规范，具备时序连续性、空间多点和数值精确三大特征，适用于家庭能耗分析、温控策略优化、热舒适性评估及智慧家居系统建模等应用场景。

This dataset is titled "Multi-point Temperature Time-series Monitoring Data for Residential Buildings in Shanghai". It records real-time temperature changes at five distinct locations within a typical residential bedroom in Shanghai over a unified time series. The dataset covers a continuous monitoring period from 8:18:58 on December 5, 2025, to 1:13:12 on January 29, 2026, with a total of 76,326 records collected at a second-level frequency, forming an observed temperature field sequence with high temporal resolution.

The data is organized in a tabular format, consisting of 7 fields:
1. ID (Serial Number): Unique integer identifier for each record, incrementing starting from 1.
2. time (Timestamp): Collection moment, formatted as "YYYY-MM-DD HH:MM:SS" with precision down to the second.
3. t0 (Temperature at Sensor 0): Unit is degrees Celsius (℃), floating-point type with a precision of 0.01℃.
4. t1 (Temperature at Sensor 1): Unit is degrees Celsius (℃), floating-point type with a precision of 0.01℃.
5. t2 (Temperature at Sensor 2): Unit is degrees Celsius (℃), floating-point type with a precision of 0.01℃.
6. t3 (Temperature at Sensor 3): Unit is degrees Celsius (℃), floating-point type with a precision of 0.01℃.
7. t4 (Temperature at Sensor 4): Unit is degrees Celsius (℃), floating-point type with a precision of 0.01℃.

All temperature data are measured values, reflecting dynamic changes at various indoor spatial positions (e.g., near windows, near doors, central bedroom areas, etc.) under both natural and artificial temperature regulation. The dataset has a clear structure and standardized fields, with three core characteristics: temporal continuity, multi-point spatial coverage, and accurate numerical values. It is suitable for application scenarios such as residential energy consumption analysis, temperature control strategy optimization, thermal comfort assessment, and smart home system modeling.

搜集汇总

背景与挑战

背景概述

当前内容展示的是上海市数据产品知识产权登记管理系统的公示列表，其中包含一系列由赣州市章贡区文化广电旅游局申请的非物质文化遗产相关数字化产品。这些产品主要涉及绳编、钩针、根雕等传统工艺的高精度三维数字模型，属于数据加工集合类型，用于文化保护和展示。