Agriculture, one of the oldest sectors of humanity, is undergoing an unprecedented transformation thanks to the advent of digital technologies.
Agriculture 4.0 represents the digital evolution of the agricultural sector, based on the integration of advanced technologies such as IoT sensors, drones, robots, decision support systems (DSS), artificial intelligence, cloud computing, and edge computing. Its main goal is to optimize resources and improve productivity while reducing waste, costs, and environmental impact (Osservatori.net; Agrifood.Tech)
According to the Italian Ministry of Agriculture, Agriculture 4.0:
“Consists of a set of digital and automation technologies that enable precise and sustainable management of agricultural activities, supported by data collected from connected machines and devices.” (Cluster Agrofood Lombardia, 2025)
In the beginning, agricultural sensors were simple and poorly connected devices, mainly used to measure temperature, soil moisture, or rainfall levels.
Data was collected manually or via local stations and served more for documentation than for real-time action.
This stage represented an embryonic form of precision, but without automation or predictive capabilities (Il Sole 24 Ore).
With the spread of wireless networks (LoRa, NB-IoT, 4G, and now 5G), agricultural sensors made a qualitative leap forward.
Sensors evolved into intelligent IoT devices, capable of collecting and transmitting real-time data on physical, chemical, and biological parameters (Digitech.News; Wikipedia LoRa).
This development paved the way for more timely, automated, and predictive farming.
Today, sensors not only read the environment but also communicate with each other, with tractors, drones, and cloud platforms.
Artificial intelligence processes the collected data to provide predictive advice: when to irrigate, when to treat, when to harvest (Quaderni Agricoltura Piemonte).
Some systems leverage edge computing for in-field processing and machine learning to detect water stress, nutrient deficiencies, or diseases (Wikipedia Edge Computing).
When we think of agricultural sensors, we usually consider soil, water, or plants. But there is a key environmental variable often underestimated: air.
Real-time monitoring of temperature, relative humidity, atmospheric pressure, CO₂, VOCs (volatile organic compounds), particulate matter, and air quality can provide crucial insights to prevent biotic and abiotic stress, fungal diseases, or microclimatic fluctuations that directly affect productivity.
Air is also an early indicator: variations in temperature and humidity, for example, can anticipate the development of powdery mildew or downy mildew in vineyards, or alternaria in horticulture (Digitech.News).
In this context, our atmospheric monitoring sensors come into play, designed specifically for precision agriculture: devices capable of accurately measuring microclimatic parameters, transmitting data in real time, and integrating with DSS to optimize irrigation, crop protection, and ventilation in tunnels or greenhouses.
The future of agriculture depends on the air we breathe and the data we know how to interpret.
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