Can LoRaWAN Networks Transform the Indian Meteorological Department into a World Leader in the Fight Against Global Warming?

Advantages of LoRaWAN Star-on-Star vs. LTE, GSM, NB-IoT, CAT-M1 and others:

• Extend wireless network coverage 10+ km past existing LTE, GSM, NB-IoT, CAT-M1 coverage with LoRaWAN LTE gateways

• LoRaWAN gateway affordability ensures deployment of double and triple-redundant wireless networks affordably due to its Star-on-Star approach vs. mesh networking.

• Meteorological sensor nodes communicate with multiple gateways, ensuring reliability of wireless data transmission and interference resistance. In case of a gateway failure, data is automatically rerouted via other gateways.

• LoRaWAN networks allow the addition of unlimited nodes without rebuilding the wireless infrastructure.

• LoRaWAN networks naturally permit network expansion and do not require trained personnel in the field to support network operation since gateways act as only message forwarders (data pass-through) and sensor nodes do not join/pair with gateways, but directly with the application running at the Met Department.

WMO Precision Wireless LoRaWAN Meteorological Sensors

For meteorological network building to the highest WMO measurement standards.

• MeteoWind® IoT Pro exceeds WMO/NWS standards by 5X, making it maintenance free for a lifetime.

• MeteoHelix® IoT Pro meets WMO/NWS standards and due to its helical shield is maintenance free for 2X longer than any other temperature humidity sensor solution.

• MeteoRain® IoT Compact is designed for high-density deployment and affordability. Its measuring mechanism is more accurate than any other rain gauge under 1000 EURO. Soon to be released MeteoRain® IoT Pro with a larger and taller collector bucket will exceed all WMO and NWS measurement standards.

MeteoHelix® IoT Pro - LoRaWAN Micro-Weather Station

from €623.00

CURRENTLY SHIPPING WORLDWIDE

Professional all-in-one wireless micro-weather station ensures your measurements comply with WMO/NWS accuracy standards. Built into the helical MeteoShield® Professional to provide significantly lower air temperature uncertainties than any other all-in-one or compact weather station on the market. Designed for professional meteorological network building, smart-cities, resilient city initiatives in all-climates from Antarctica to the Deserts of Rajasthan.

Rain Gauge:

Select Rain Gauge Without Rain GaugeMeteoRain 200 Compact (PREORDER)With cable (for rain gauge)

Without Rain Gauge MeteoRain 200 Compact (PREORDER) With cable (for rain gauge)

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MeteoWind® IoT Pro - LoRaWAN

from €499.00

Compact wind sensor meeting the highest MEASNET accuracy requirements. Exceeds WMO and NWS specifications by a factor of 5, thus it can be considered maintenance free for a lifetime in most meteorological applications. Compared to ultrasonic anemometers, it offers faster response time at wind speeds greater than 4 m/s, thus its able to accurately capture even the shortest wind gusts. It has higher data availability that ultrasonic wind sensors in harsh stormy and winter weather.

Wireless unit cable length:

Select Wireless unit cable length 5 meter10 meter

5 meter 10 meter

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Wireless MeteoRain® IoT Compact -LoRaWAN

€324.00

Next ship date: April 2021

Wireless Ø200 cm² professional compact gauge for agriculture, smart-cities and research with 5+ years of battery life. Low maintenance rain gauge for agriculture and smart cities where long-term maintenance-free operation is essential. Uses a self-balancing magnetic tipping bucket measuring principle to reduce or resist the effects of dirt, vibration and leveling errors.

Rain resolution:

Select Rain resolution WORLD: 0.2 mm/tipUSA: 0.01 inch/tip

WORLD: 0.2 mm/tip USA: 0.01 inch/tip

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Zu vermeidende Smart-City-Fehler: die Frage der großen gegen genaue Daten

DIE SMART-CITY-FEHLER DIE ZU VERMEINDEN SIND: DIE QUALITÄT VON DATENSÄTZEN MIT NIERIGER QUALITÄT WIRD NICHT VERBESSERT, WENN DIE DATENSÄTZE GRÖßER WERDEN

Wenn Sensornetzwerke nicht dem grundlegenden Messstandards entsprechen, werden Smart-City-Sensornetzwerke zu einem Geldfresser. Sie können großartige Ideen in eine sinnlose Infrastruktur und Wolken von falschen oder bedeutungslosen Daten verwandeln.

Zu Beginn des 21. Jahrhunderts begannen Städte im Rahmen der vierten industriellen Revolution (Industrie 4.0), mit Smart-City-Projekten zu experimentieren, noch bevor der Begriff Internet-of-Things (IoT) populär wurde. Jetzt, auf dem Höhepunkt des durch künstliche Intelligenz und Datenverarbeitung ausgelösten IoT-Hype, werden die ersten Anzeichen für die Notwendigkeit, die grundlegenden Messstandards von  NIST, WMO/CIMO, NWS/NOAA, ASTM und ISO zu treffen, offensichtlich.

Das klarste Beispiel für die Notwendigkeit, grundlegende Messstandards zu treffen, kann man in Überwachung des Stadtklimas finden, da die Städte eine Reihe von Herausforderungen an die genaue Messung der Lufttemperatur stellen. Die Fußwege und Gebäudewände in der Nähe von Wetterstationen reflektieren und strahlen Sonnenenergie viel stärker als Grasrasen und aus jeder Richtung auf einen Temperatursensor ab, was zu großen Fehlern bei der Lufttemperaturmessung führt. Da die Verteilung der Fehler bei der Lufttemperaturmessung nicht symmetrisch rund um tatsächlichen Temperaturwert und für jede Wetterstationsinstallation einzigartig ist, hat die Praxis gezeigt, dass sich die Qualität von Daten geringer Qualität nicht mit der Größe des Datensatzes verbessert.

Die Qualität der Lufttemperaturmessung kann leicht beurteilt werden, indem die Sonneneinstrahlung (W / m²) und die Lufttemperatur (° C / ° F) zusammen eingezeichnet werden. Lufttemperatursensoren niedriger Qualität zeigen zusammen mit billigen Sonnenschutzschildern eine Erhöhung der Lufttemperatur um +0,5 ° C (+1 ° F) oder mehr innerhalb weniger Minuten, nachdem die Sonne von hinter her Wolken oder die Wetterstation aus dem Schatten hervorkommt.

Manufacturer of high-quality and affordable meteorological solutions for Smart-City environmental sensor networks including the MeteoHelix IoT, MeteoRain IoT and MeteoWind IoT wireless weather station and sensors.

Smart-City Mistakes to Avoid: The Question of Big-Data vs. Accurate-Data

Smart-City Mistakes to avoid: quality of low-quality data sets does not improve as the data set gets bigger

When sensor networks don’t meet basic standards of measurement, smart-city sensor networks become bottomless money pits. They can turn great ideas into senseless infrastructure and clouds of deceitful or meaningless data.

Early in the 21st-century, cities started experimenting with Smart-City projects as part of the fourth industrial revolution (Industry 4.0) even before the phrase Internet-of-Things (IoT) became popularized. Now, at the current peak of the IoT craze fueled by artificial intelligence and data-processing hype, the first signs of a need to meet basic measurement standards of NIST, WMO/CIMO, NWS/NOAA, ASTM and ISO are becoming apparent.

The clearest example of the need to meet basic measurement standards can be found in urban climate monitoring since cities pose a number of challenges to accurate air temperature measurement. Pavement and building walls in the vicinity of weather stations reflect and radiate solar energy much more than grass turf and from every direction onto a temperature sensor causing large errors of air temperature measurement. Since the distribution of errors in air temperature measurement is not symmetric around the real-temperature value and is unique for each weather station installation, practical experience has shown that the quality of low-quality data does not improve with data set size.

Quality of air temperature measurement can be easily assessed by plotting together sunshine intensity (W/m²) and air temperature (°C/°F). Low-quality air temperature sensors, together with cheap solar radiation shields, show an increase in air temperature of +0.5 °C (+1 °F) or more within a few minutes of the sun coming out from behind clouds or the weather station coming out of a shadow.

Manufacturer of high-quality and affordable meteorological solutions for Smart-City environmental sensor networks including the MeteoHelix IoT, MeteoRain IoT and MeteoWind IoT wireless weather station and sensors