## 6 Conclusions and Future Work  
In this work, the implementation of a cost-effective and portable instrument, which enables accurate pH measurements for global _Vertical Farming_ applications, has been described. By performing a well-designed calibration of the sensor, near Nernstian response, in this case 57.56 [mV/pH], was demonstrated. The instrumentation was compared to a laboratory gold standard, which is at least ten times more expensive, and was shown to be accurate in determining the pH of substances in the 2-14 range. Furthermore, the  
Figure 8: The signal conditioning stage can be improved by optimizing the usable detection range of the ADC. We propose to modify the feedback resistor and the (fixed) voltage divider network resistor to improve the performance by a two-fold factor: from 48 to 98% usable detection range.  
instrument yields precise pH results with an average absolute deviation of 0.06 pH units and a standard deviation of 0.03 pH units. Compared to previous research efforts, the instrumentation is unique because it incorporates a three-layer IoT architecture with _Perception_, _Network_, and _Application_ Layers. Additionally, the design is optimal for worldwide adoption by consisting of four modular stages: sensing, signal conditioning, signal acquisition, and communications. The design of the instrument was shown to be ADC-limited, with a minimum detectable value of 0.028 pH units, and a typical absolute accuracy of \(\pm\)0.062 pH units. In order to overcome this limitation, a means to improve performance was presented by meticulously designing the bias and amplification circuitry of the signal conditioning stage, and by optimizing the signal acquisition section of the instrument. The next steps in our research include the implementation of an AI algorithm to detect and compensate for mechanical instabilities of the instrument, and to incorporate other critical sensors, such as total dissolved solids meters, for VF applications.  
The calibration code information can be downloaded at: [[https://pabellon.tecnm.mx/LIA/productos_generados.html#Trabajos_realizados](https://pabellon.tecnm.mx/LIA/productos_generados.html#Trabajos_realizados)]([https://pabellon.tecnm.mx/LIA/productos_generados.html#Trabajos_realizados](https://pabellon.tecnm.mx/LIA/productos_generados.html#Trabajos_realizados)) (accessed on 30 June 2022).  
Conceptualization, R.H.-M., E.O.-G. and P.V.-J.; methodology, R.H.-M., E.O.-G. and P.V.-J.; software, R.H.-M., N.E.-G. and M.M.R.; validation, R.H.-M., E.O.-G. and P.V.-J.; formal analysis, R.H.-M., E.O.-G., N.E.-G., J.A.D.-A., M.M.R. and P.V.-J.; research, R.H.-M., N.E.-G. and P.V.-J.; resources, [PERSON], [PERSON] and [PERSON]; data curation, [PERSON], [PERSON] and [PERSON]; original drafting, [PERSON], [PERSON] and [PERSON]; drafting-revising and editing, [PERSON], M.M.R., [PERSON] and [PERSON]; visualization, [PERSON], [PERSON] and [PERSON]-[PERSON]; supervision, [PERSON], [PERSON], [PERSON], M.M.R. and [PERSON]; project management, [PERSON], [PERSON], [PERSON] and [PERSON]; fund raising, E.O.-G. and N.E.-G. All authors have read and agreed to the published version of the manuscript.  
We acknowledge the support of the Consejo Nacional de Ciencia y Tecnologia (CONACYT) in Mexico for supporting this work through funds for projects INFRA-2016-01, Project No. 270665. CB-2016-01, Project No. 287818. Additionally, we acknowledge the support to the Government of the State of Aguascalientes, and the Instituto para el Desarrollo de la Sociedad del Conocimiento del Estado de Aguascalientes (IDSCEA) through the Technological Innovation Fund for projects FEIT-AGS-2020-20-17, FEIT-AGS-2020-20-18 and 029-FEIT-2021.  
Not applicable.  
The authors declare no conflict of interest.