**5. Conclusions**

Careful resource managemen<sup>t</sup> is becoming more and more relevant due to frequent extreme meteorological events, such as droughts. Therefore, a non-invasive system of sensors that can inspect the conditions of the plants in near-real time, with high resolution and reliability, represents a valid tool to optimize resource consumption.

The extensive monitoring of the plant's health can be achieved through climatic data detection, which can, in turn, be exploited to evaluate the Crop Water Stress Index, a vegetation index related to the ability of the plant to exploit the available water. The focus on CWSI is dictated by the current desertification trend that leads to hotter and drier summers, especially in the temperate regions where viticulture is extensively diffused (e.g., Italy and France). Due to this change in climate, equipping crops with irrigation systems balancing the lack of rainfall and keeping the crop in the optimal condition of Water Stress will become fundamental, and a close monitoring of the critically stressed areas could lead to better resource management.

Through this non-invasive monitoring system, it is possible to draw maps of georeferenced CWSI on crop areas. The maps offer a resolution, precision, time and operational cost more convenient than a human operator or a satellite without altering the vineyard structure or obstructing the cultivation operations.

With an on-field data collection session, the working principle of the system has been validated through a prototype, and high-resolution CWSI maps have been obtained. Through sensitivity analysis, it has been possible to determine which climatic variables affect the CWSI the most: these variables need to be detected with the most reliable sensors and with the highest possible resolution. The sensitivity analysis has offered an insight into system improvements that would entail both fixed and moving sensors: the former for the variables that can be taken as an average over the whole crop and the latter for the variables that need a higher resolution.

Further validation is needed to better study the correlation between the values of CWSI obtained with the on-field sensors and the ones obtained through satellite data taken by the Copernicus database and Landsat Satellite. Furthermore, the moving sensors could be mounted on autonomous drones to completely automatize the data collection step and create a full system that collects and analyses the data and offers as an output an easy-to-read map of the crop.

Finally, if the system is implemented on a crop for a long enough time span, a new intriguing possibility could be the correlation of the CWSI trend with the seasonal vineyard productivity and final grapes' organoleptic quality. These future developments are beyond the scope of this paper and will be investigated in further studies.

**Author Contributions:** Conceptualization, all; methodology, P.B.d.P., G.B., A.B., C.G., L.M., M.M. and G.N.; software, C.G., L.M. and G.N.; validation, P.B.d.P., G.B., A.B., C.G., L.M., M.M. and G.N.; data curation, C.G. and G.N.; writing—original draft preparation, P.B.d.P., G.B., A.B., C.G., L.M., M.M. and G.N.; writing—review and editing, all; visualization, L.M.; supervision, V.C., C.C., S.I. and S.M.; project administration, L.M. and S.M.; funding acquisition, V.C., C.C., S.I. and S.M. All authors have read and agreed to the published version of the manuscript.

**Funding:** The financial support by Alta Scuola Politecnica to the Multidisciplinary Project "AIS4SIA: Artificial Intelligent Systems for a Smart and Innovative Agriculture" is gratefully acknowledged.

**Institutional Review Board Statement:** Not applicable.

**Informed Consent Statement:** Not applicable. **Data Availability Statement:** The data presented in this study are available on request from the corresponding author.

**Conflicts of Interest:** The authors declare no conflict of interest.
