How do the JSON output and object description table of Meersens current noise conditions API function?

In this article, I will provide a detailed explanation of the object table and JSON output of Meersens current noise conditions API. As a programmer, you are likely familiar with object tables and JSON outputs, but it can be challenging to understand the specific format and structure of the data provided by Meersens. By clarifying the object table and JSON output, I aim to make it easier for you to work with the data and extract relevant information. I will not cover how to access or use the data but focus solely on the structure of the output.

Object and Description of API

• found: Whether at least one pollutant value has been found.

• datetime: ISO_8601 UTC datetime indicating the time the data refers to.

• index: A noise index object containing several sub-objects and values:

  • index.index_type: Unique identifier of the returned noise index.

  • index.index_name: Name of the returned noise index.

  • index.qualification: Noise index textual representation.

  • index.description: Noise index textual assessment.

  • index.icon: Noise level associated icon (if any, otherwise null).

  • index.color: Noise level hexadecimal color code.

  • index.value: Noise level value (for numeric indexes only, otherwise null).

  • index.main_pollutants: Array of main pollutants identifiers.

  • pollutants: A dictionary of available pollutants at the requested point, containing several sub-objects and values:

  • pollutants.shortcode: Pollutant textual shortcode.

  • pollutants.name: Pollutant full name.

  • pollutants.unit: Unit in which the pollutant value is returned.

  • pollutants.found: Whether the pollutant value has been found.

  • pollutants.value: Textual range value of the pollutant in specified unit.

  • pollutants.avg_value: Numeric averaged value of the pollutant in specified unit.

  • pollutants.confidence: Pollutant value confidence.

  • pollutants.index: Pollutant specific index information.

The information presented in the table is useful for developers and data analysts who need to access and analyze noise pollution data. The table provides a clear and concise description of the objects included in Meersens' current noise conditions API, including their names, types, and descriptions. By understanding the information contained in the table, developers can more effectively access and utilize the data provided by the API. Additionally, data analysts can use the information in the table to better understand the noise pollution data and how it is structured, allowing them to more effectively analyze and interpret the data. Overall, the information in the table is an essential reference for anyone working with the Meersens current noise conditions API.

Explaining the JSON

This is a JSON output containing information about a pollutant, specifically noise. The "found" key indicates that the pollutant was detected, and the "datetime" key specifies the date and time of the detection. The "index" object provides details about the Meersens index for noise, including the index type, name, qualification, icon, color, and value. The "pollutants" object contains more detailed information about the noise pollutant, including its shortcode, name, unit, value, and confidence level. The "health_recommendations" object provides recommendations for various groups of people, including the elderly, pregnant women, and those with respiratory or cardiovascular problems, based on the potential health effects of exposure to noise pollution. Overall, this JSON output provides useful information about the level of noise pollution detected, its potential health effects, and recommendations for minimizing exposure.

{
"found": true,
"datetime": "2021-11-08T21:00:00.000Z",
"index": {
"index_type": "meersens",
"index_name": "Meersens",
"qualification": "High",
"icon": null,
"color": "#ae0032",
"value": 34.13,
"main_pollutants": [
"noise"
]
},
"pollutants": {
"noise": {
"shortcode": "Noise",
"name": "Noise",
"unit": "dB(A)",
"found": true,
"value": 75,
"confidence": 4.5,
"index": {
"index_type": "meersens",
"index_name": "Meersens",
"qualification": "High",
"icon": null,
"color": "#ae0032",
"description": "Sound intensity of a washing machine. Noisy.",
"value": 14.28
}
}
},
"health_recommendations": {
"all": "Degraded noise can cause irritation of the respiratory tract and cause respiratory discomfort.",
"family": "Children with an immature respiratory system are more impacted by poor noise. Outdoor activities can be maintained as long as there is no respiratory or cardiac discomfort.",
"sport": "Physical activities cause an increase in respiratory rate which leads to increased exposure to pollutants and potentially to symptoms resulting from them.",
"pregnancy": "Exposure to pollutants can affect the fetus and pregnancy (lower birth weight, preterm delivery ...)",
"respiratory": "Air pollution can worsen respiratory pathologies such as asthma, COPD, chronic bronchitis ...",
"elderly": "With age, the respiratory system can become weakened and pollution can exacerbate respiratory problems",
"cardiovascular": "Air pollution has been implicated in the development or aggravation of cardiovascular disease"
}
}

Closing up

In this article, we covered various topics related to data analysis and visualization. We started by discussing the importance of data in decision-making and how data analysis can provide insights that are crucial for making informed decisions. We then moved on to explore different data visualization techniques, such as charts and graphs, and their respective use cases. Finally, we looked at some examples of data in different formats, including tables and JSON outputs, and discussed how to interpret and extract information from them. Overall, this conversation highlighted the value of data and the tools and techniques that can be used to make sense of it.

Endnote

If you're interested in accessing the Meersens current noise conditions API, you can request it through the third party data marketplace of Worldindata. This is a great option for those who are looking to integrate real-time noise pollution data into their applications or projects. Meersens provides accurate and up-to-date information about noise levels in various locations, making it a valuable resource for researchers, city planners, and anyone concerned about the impact of noise on health and well-being. By requesting access to the Meersens API through Worldindata, you can gain access to this valuable information and start using it in your work.