###### Abstract
(2018) showed that there has been an increasing public awareness of real-time air quality recently because air pollution can have serious impacts on human health and the environment. In their study, they presented a cost-effective and portable air quality measurement system using an Arduino Uno microcontroller and four low-cost sensors. This device allows the concentration of carbon monoxide, ground-level ozone, and particulate matter (PM\({}_{10}\) and PM\({}_{2.5}\)) in the air to be measured anywhere. In their study, [PERSON] et al. (2018) showed that the Raspberry Pi microcontroller, to which different sensors such as the MQ7 and DHT11 and dust density sensors were connected, plays an important role in checking the status of the environment. It detects the level of carbon dioxide and carbon monoxide, temperature, relative humidity, and dust particles present in the environment. Furthermore, probe data were stored and digitally analyzed when necessary, and various results were extracted. In a study by [PERSON] (2018), sensors were used to measure carbon monoxide and carbon dioxide levels, dust density, and nitrogen oxide concentration. These sensors were connected to an Arduino board, and the measurements were used to determine air quality; these data were sent to a smartphone. For use in time series studies of acute health consequences, a robust methodology was devised to compute population-weighted daily measurements of ambient air pollution ([PERSON], 2018). Therefore, the present study aimed to develop a portable device to quantify the amount of air contaminants in the atmosphere, which were measured using an MQ7 sensor and a GP2Y1010 AU0F sensor; however, all sensors were linked to an Arduino board. Moreover, weather variables were measured by a DHT11 temperature and relative humidity sensor and a BMP180 barometric pressure sensor. Additionally, this study aimed to develop an integrated indicator of the air quality pollution level called an integrated indicator for air quality assessment (IAQA). It was dependent on weather variables and other variables related to air quality. The IAQA can be used to compare agricultural environments in terms of their air quality. The calculation depends on the value of the weight assigned to each of the variables, such as carbon monoxide concentration, dust concentration in the air, air temperature, air relative humidity, and atmospheric pressure. These variables were measured using sensors connected to an Arduino board. The novel aspect is to link indicators of air pollutants to meteorological parameters for the development of a new criterion, represented by the Integrated Indicator for Air Quality Assessment (IAQA). It was also proposed that the indexes of air pollutants and climatic parameters be linked to assess air quality under certain agricultural conditions. Finally, it also reports new outcomes on the integration of different types of farm activities with air pollutants and weather parameters, thus showing their contribution to the levels of air quality. Hence, the novel methodology serves as a contribution to the existing literature as it gives new insight into the estimate and improvement of air quality in agricultural environments.