## 6 Conclusions  
The implementation of a multi-sensor air quality monitoring system in livestock facilities represents a significant advance in the management of conditions in livestock barns. The importance of multi-sensor integration lies in its ability to provide a comprehensive, real-time snapshot of air quality, overcoming the limitations of traditional single-parameter monitoring systems. By simultaneously measuring various pollutants and environmental factors, this system offers unparalleled insight into pollution sources, synergistic relationships, and the dynamic nature of air quality. Our system adheres to SOLID principles, ensuring its robustness, scalability and easy maintenance. This is an improvement over existing air quality monitoring solutions, which often lack the flexibility and durability required for effective long-term use in diverse and challenging livestock environments. By integrating sensors for ammonia, hydrogen sulfide, carbon dioxide, particulate matter (PM2.5 and PM10), total volatile organic compounds (TVOC), temperature, humidity, and pressure, our system offers a holistic view of air quality conditions, supporting agricultural manufacturers with the data needed to make informed decisions. In addition, the multi-sensor system we developed is cost-effective using low-cost sensors and open-source tools, which significantly reduces the overall cost of the system. This aspect makes our solution more affordable and practical for widespread distribution in various agricultural settings, especially in regions with limited resources. Compared to other expensive air quality monitoring systems, our approach offers a viable and sustainable alternative without compromising data accuracy and reliability. Future developments focus on further reducing costs and integrating advanced data analysis techniques such as artificial intelligence and machine learning. These improvements will allow the prediction of air quality trends and identify potential animal hazards before they become critical problems. Furthermore, improving the system's robustness to different environmental conditions and ensuring its adaptability to different livestock settings will be essential for wider application. Conceptualization, V.D., K.D. and T.A. ; methodology, V.D., K.D. and T.A. ; writing--original draft preparation, V.D., K.D. and T.A. ; writing--review and editing, V.D., K.D. and T.A. All authors have read and agreed to the published version of the manuscript. The research leading to these results received funding from the Ministry of Education and Science of the Republic Bulgaria under the National Science Program INTELLIGENT ANIMAL HUSBANDRY, grant agreement No. \(\mathcal{I}\)01-62/18.03.2021/. Not applicable. [PERSON] [PERSON]; [PERSON]; [PERSON] [PERSON]; [PERSON]; [PERSON]. Low-Cost Air Quality Sensing towards Smart Homes. _Atmospheric_**2021**, _12_, 453. [CrossRef]
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