IoT is one of the few industries that deal with high volume, high stake, high-risk, and high-streaming data. It is a complex and complicated medium and involves hundreds of data points at the same time. For this reason, the management of microsensors and their related data is a crucial step that is involved in the day-to-day IoT process.
Capturing this high volume and volatile data and maintaining synchronization between various data points is not an easy task at all. Moreover, if you tried to gather all the data sources and build a centralized platform for yourself, would probably take you enormous amounts of time and effort to implement the solution. In addition, it is unlikely that it would be optimized to address all of your data points.
Weather data also encounter frequent changes and all the systems that depend on it must be immediately notified of the changes. This is in order to avoid any mishaps or irregularities. For instance, you may have an IoT-driven temperature controlling system at your factory to automatically manage the temperature level and trigger automatic alarms and warnings in case of irregularities. As you can imagine, in this case, incorrect information could result in a lot of damage. Consequently, the accuracy of IoT data is a sensitive area and must be dealt with carefully.
The weatherstack is a third-party world weather API service that gives you access to real-time and historical world weather data. Furthermore, it can retrieve instant and accurate weather information for any area in the world. Finally, the weatherstack API is highly available and is widely trusted due to its rock-solid uptime and speed.
Read on to learn how you can easily fetch weather data to build a powerful IoT-driven temperature controlling unit using weatherstack and Flask framework.
How can I start my IoT-driven temperature unit based on the current weather situation?
Worried about manually monitoring the weather and then activating/deactivating your temperature controlling system? By integrating weatherstack APIs with your IoT system, you can easily and automatically control its behavior based on your preferred data points.
To query the weatherstack API for real-time weather data in a location of your choice, simply attach your preferred location to the API’s current endpoint as seen in the example request below. Next, depending on your subscription, you can also make a bulk location request by passing multiple semicolon-separated locations to the API URL.
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import requests from flask import jsonify @app.route('/temperature_unit/start/') def start_temperature_unit(): params = { 'access_key': 'YOUR_ACCESS_KEY', 'query': 'New York' } api_result = requests.get('https://api.weatherstack.com/current', params) weatherstack_response = api_result.json() # write your custom logic here... return { 'status': true, 'metadata': weatherstack_response } |
How can I manage heat cycles using predictive analysis?
Based on the previous weather trends, you can quickly figure out your next heat cycle using the power of predictive data analysis.
To look up historical weather data all the way back to 2008, simply pass one date of your choice (later than July 2008) or multiple semicolon-separated dates to the weatherstack API’s historical endpoint using the historical_date parameter.
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import requests from flask import jsonify @app.route('/heat_cycles/manage/') def manage_heat_cycles(): params = { 'access_key': 'YOUR_ACCESS_KEY', 'query': 'New York', 'historical_date' = '2015-01-21', 'hourly' = 1 } api_result = requests.get('https://api.weatherstack.com/historical', params) weatherstack_response = api_result.json() # write your custom logic here... return { 'date': '2015-01-21', 'metadata': weatherstack_response } |
How can I schedule the temperature control system for service maintenance based on the weather forecast?
Using weatherstack’s powerful forecasting engine, you can also figure out the possibilities for natural heat availability and send your temperature control unit for scheduled maintenance and recovery.
In addition, weatherstack is capable of returning weather forecast data for up to 14 days into the future. In order to get weather forecasts, simply use the API’s forecast and define your preferred number of forecast days using the forecast_days parameter.
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import requests from flask import jsonify @app.route('/service_maintenance/schedule/') def schedule_service_maintenance(): params = { 'access_key': 'YOUR_ACCESS_KEY', 'query': 'New York', 'forecast_days' = 1, 'hourly' = 1 } api_result = requests.get('https://api.weatherstack.com/forecast', params) weatherstack_response = api_result.json() # write your custom logic here... return { 'forecast_days': 1, 'metadata': weatherstack_response } |
As you can see, automating your IoT devices with accurate weather data using weatherstack is extremely simple and easy. Not only that, weatherstack is reliable and is also easy on your budget. As a result, it can help you affordably automate your systems. Moreover, the weatherstack free plan is the ideal choice for experimentation, trials, and proof of concepts.
