Environmental Sensor Telemetry Data

### Context

Environmental sensor telemetry data, detailed in the blog post, [Getting Started with IoT Analytics on AWS](http://tinyurl.com/iot-analytics-aws), published on [Towards Data Science](https://towardsdatascience.com).

### Content

The data was generated from a series of three identical, custom-built, breadboard-based sensor arrays. Each array was connected to a Raspberry Pi devices. Each of the three IoT devices was placed in a physical location with varied environmental conditions.

```text
| device | environmental conditions |
|-------------------|------------------------------------------|
| 00:0f:00:70:91:0a | stable conditions, cooler and more humid |
| 1c:bf:ce:15:ec:4d | highly variable temperature and humidity |
| b8:27:eb:bf:9d:51 | stable conditions, warmer and dryer |
```

Each IoT device collected a total of seven different readings from the four sensors on a regular interval. Sensor readings include temperature, humidity, carbon monoxide (CO), liquid petroleum gas (LPG), smoke, light, and motion. The data spans the period from __07/12/2020 00:00:00 UTC__ – __07/19/2020 23:59:59 UTC__. There is a total of __405,184__ rows of data.

The sensor readings, along with a unique device ID and timestamp, were published as a single message, using the ISO standard Message Queuing Telemetry Transport (MQTT) network protocol. Below is an example of an MQTT message payload.

```json
{
"data": {
"co": 0.006104480269226063,
"humidity": 55.099998474121094,
"light": true,
"lpg": 0.008895956948783413,
"motion": false,
"smoke": 0.023978358312270912,
"temp": 31.799999237060547
},
"device_id": "6e:81:c9:d4:9e:58",
"ts": 1594419195.292461
}
```

### Columns

There are nine columns in the dataset.

```text
| column | description | units |
|----------|----------------------|------------|
| ts | timestamp of event | epoch |
| device | unique device name | string |
| co | carbon monoxide | ppm (%) |
| humidity | humidity | percentage |
| light | light detected? | boolean |
| lpg | liquid petroleum gas | ppm (%) |
| motion | motion detected? | boolean |
| smoke | smoke | ppm (%) |
| temp | temperature | Fahrenheit |
```

### Detail Image of Sensors

### 上下文
环境传感器遥测数据，详细描述于博客文章《在 AWS 上开始 IoT 分析》（[Getting Started with IoT Analytics on AWS](http://tinyurl.com/iot-analytics-aws)），发表于 [Towards Data Science](https://towardsdatascience.com)。

### 内容
该数据由一系列三个相同的、基于面包板定制的传感器阵列生成。每个阵列连接到 Raspberry Pi 设备。三个物联网设备分别放置于具有不同环境条件的物理位置。

| 设备 | 环境条件 |
|-----------------|-----------------------------------------------------------------
| 00:0f:00:70:91:0a | 稳定条件，较凉爽且湿度较高 |
| 1c:bf:ce:15:ec:4d | 温度和湿度高度可变 |
| b8:27:eb:bf:9d:51 | 稳定条件，较温暖且干燥 |

每个物联网设备定期从四个传感器收集总共七个不同的读数。传感器读数包括温度、湿度、一氧化碳（CO）、液化石油气（LPG）、烟雾、光线和运动。数据时间跨度为 __07/12/2020 00:00:00 UTC__ – __07/19/2020 23:59:59 UTC__。总共有 __405,184__ 行数据。

传感器读数、唯一设备 ID 和时间戳以单个消息的形式发布，使用 ISO 标准的消息队列遥测传输（MQTT）网络协议。以下是一个 MQTT 消息负载的示例。

{
"data": {
"co": 0.006104480269226063,
"humidity": 55.099998474121094,
"light": true,
"lpg": 0.008895956948783413,
"motion": false,
"smoke": 0.023978358312270912,
"temp": 31.799999237060547
},
"device_id": "6e:81:c9:d4:9e:58",
"ts": 1594419195.292461
}

### 列
数据集中包含九列。

text
| 列 | 描述 | 单位 |
|------|--------------------|------------|
| ts | 事件时间戳 | 纪元 |
| device | 唯一设备名称 | 字符串 |
| co | 一氧化碳 | ppm (%) |
| humidity | 湿度 | 百分比 |
| light | 检测到光线？ | 布尔值 |
| lpg | 液化石油气 | ppm (%) |
| motion | 检测到运动？ | 布尔值 |
| smoke | 烟雾 | ppm (%) |
| temp | 温度 | 华氏度 |

### 传感器细节图像