International Journal of Engineering Insights: (2023) Vol. 1, Nro.1, Regular Paper

https://doi.org/10.61961/injei.v1i1.5

Acidity analysis in diﬀerent blackberry dilutions using IoT

Eduardo Teneda · Lorena C´aceres

Received: 5 July 2023 / Accepted: 3 October 2023

Abstract: The internet of things has expanded to all

areas, including the food ﬁeld, seeking to guarantee

food and analyze its characteristics remotely. In this

work, an electronic system is developed that allows real-

time measurements and analysis of pH and temperature

and controls a mixer from a mobile application. The

electronic design consists of a servomotor (Mixer) and a

pH and temperature sensor (pH 4502C) connected to an

ESP32 board. In the experiments, the blackberry fruit

pulp was used in beakers with dilutions of 25%, 50%,

and 100%. The sensor probe was immersed in these

samples. In the results, the experiment was performed

four times so that the data were reliable; the measure-

ment was carried out ﬁrst by measuring the pH in the

water for four minutes, then the sensor probe was trans-

ferred to the beaker containing the dilutions for four

minutes. The pH and temperature data recorded are

sent through WiFi to Thingspeak and are monitored in

a mobile application designed in AppInventor, then ex-

ported the data to make decisions regarding the behav-

ior of the pH, which allows identifying if the blackberry

has the necessary conditions for humans’ consumption.

Keywords pH sensor · Blackberry · ESP32 ·

IoT.acidity

1 Introduction

1.1 Motivation

The blackberry (Rubus glaucus) is a fruit native to

tropical South America, cultivated mainly in Colombia

and Ecuador [1]. It is rich in components such as antho-

cyanins and ellagitannins [2]. It is cultivated by farm-

ers in the Andes region and contributes signiﬁcantly

to the generation of economic resources at the level of

small and medium producers [3]. It has nutritional and

Eduardo Teneda · Lorena C´aceres

Universidad Indoam´erica

Ambato, Ecuador

lorenacaceres@uti.edu.ec

antioxidant properties appreciated by all types of con-

sumers for its pleasant color and ﬂavor, as well as for

its health beneﬁts [4]. Inadequate handling, transport

and packaging aﬀect the morphological characteristics

of the fruit [5,6], decreasing the content of bioactive

compounds [7].

It is non-climacteric fruit rich in minerals and vita-

mins that requires care during harvest and post-harvest

[8]. Its high moisture content (91%) makes it vulnera-

ble to fungal attack and its shelf life is relatively short,

ranging from 3 to 5 days, after which losses are close

to 70% [9]. Blackberry has a fragile structure [10] and

its quality decreases rapidly during the post-harvest

period, which reduces its consumption in nature [11].

The pH allows predicting the quality of the food, using

a colorimetric scale [12]. IoT allows the interaction of

machines and their control without human interaction

[13,14,15]. Through IoT, farmers can monitor factors

such as humidity, health, temperature using sensors and

without the need to go to the ﬁeld which makes the

agricultural industry more eﬃcient [16].

1.2 Related works

In the study conducted in [17], wireless transmission

technology is used with various sensors to measure tem-

perature, pH, dissolved oxygen, water level in the ﬁsh

farm. The integrated data are transmitted to mobile

devices via the Internet of Things, allowing managers

to monitor water quality. A robotic arm with a pro-

grammable logic controller, a chip combined with a

wireless transmission module and an embedded system

was developed to perform the measurements. The de-

signed intelligent measuring equipment works around

the clock, which eﬀectively reduces data losses caused

by personnel, material resources and measurement er-

rors.

In reviewing the literature, we found a work whose

objective is to implement the Internet of Things as an

information system to measure and monitor moisture,

pH, and NPK levels in mustard leaf crops with capillary

15 International Journal of Engineering Insights, (2023) 1:1

irrigation and liquid organic fertilizer. For this purpose,

a completely randomized design was used with two fac-

tors: the type of liquid organic fertilizer and the number

of capillary irrigation wicks.

The results showed that soil moisture during mus-

tard leaf growth ranged from 16.59% to 23.48%, the

higher the capillary wick, the higher the soil moisture,

the average water requirement for mustard plant growth

was 3.16 liters. The application of liquid organic fertil-

izer has a signiﬁcant eﬀect on soil pH and NPK levels

in the soil. Capillary irrigation had a signiﬁcant eﬀect

on soil pH, but had no signiﬁcant eﬀect on soil NPK

levels [18].

2 Design and Materials

To develop this proposal, a system on chip board is

used in which the programming for the operation of a

pH and temperature sensor is installed, a servo motor is

included to generate movement in the blackberry fruit

pulp that is in a 500 ml beaker where the pH probe is

immersed. The recorded pH and temperature data are

sent over the internet via an IoT platform and read into

a mobile application that employs a cloud database.

(Fig. 1 ) shows the elements used in the process.

2.1 System requirements

The requirements for the system to measure the vari-

ables and process the required information are as fol-

lows: A 500 ml beaker in which there is 350 ml of black-

berry fruit pulp. The pH-temperature sensor will mea-

sure the pH [H+] and temperature [ C] by introducing

the probe into the pulp. A servo motor is used to mix

the pulp throughout the process. Wi-Fi connectivity is

required to process the information through the Sys-

tem on chip board and to be linked through the IoT

platform so that the information can be read through

a mobile application. The system requirements can be

seen in Table 1.

2.2 Circuit and Program

The project design is based on an ESP32 board to which

the pH sensor and servo motor are connected. The To

input is connected to pin 32, Po is connected to pin 33,

G is connected to GND and uses a 3V3 power supply.

Regarding the servo motor the GND input is connected

to pin GND, the input for operation to pin 4 uses a 5V

supply. The system design is shown in (Fig. 2).

Table 1 System Requirements

Device Requirement Description Required

pH sensor

pH 0-14 value sensing

sensor module plus

BNC pH electrode

probe for value sens-

ing sensor

pH 4502C

Temperature Sensor

Temperature range:

32.0-176.0 [ F], 0 - 80

[ C].

pH 4502C

Servo Motor

Operating speed (no

load): 0.09 0.01

sec/60 (4.8 V) 0.08

0.01 sec/60 (6 V).

Operating angle: 180

degrees

Micro Servo 9g SG90

System on chip

System with Wiﬁ con-

nection, analog in-

puts, I2C communica-

tion.

ESP-WROOM-32 for

Arduino.

IoT plataform

Store, graph and pro-

cess data in the cloud.

Thingspeak

App

For smartphone,

portable, user menu

and Android operat-

ing system.

Appinventor

Precitation Glass

1.7 ﬂ. oz. thick low

form borosilicate

glass.

Precipitation beaker

with 500 ml capacity.

Fig. 1 IoT design for pH monitoring

For the programming of the pH and temperature

sensor, Arduino is used, where three libraries are in-

cluded: ESP32Servo.h, Thingspeak.h and WiFi.h, the

pH input is connected to pin 33, the temperature input

to pin 35, and the servomotor is connected to pin 4 (see

Fig. 3).

3 Connectivity and Interface

3.1 Communication

The communication is done through the ESP32 board

which has WiFi connection, the data of the measure-

ments are processed through Thingspeak where these

16 International Journal of Engineering Insights, (2023) 1:1

Fig. 2 Circuit Design

Fig. 3 Arduino Programming Code

Fig. 4 System Communication

are stored and analyzed, then the data can be observed

through the application made to in the Appinventor ap-

plication. (Fig. 4) represents the communication of the

system.

3.2 User interface

Through the Appinventor application, the user inter-

face is designed where a button for the mixing process

is shown, a section where the pH data graph is shown,

the section corresponding to the Temperature graph,

and a section corresponding to the pH graph. (Fig. 5)

shows the user interface created for the project.

4 Analysis of Results

To analyze the results, the installation of the system

was performed as shown in Fig. 6.

Fig. 5 User interface

Fig. 6 System Installation

Fig. 7 Design of Experiment

The experiment was designed using four beakers; in

the ﬁrst one we placed water (400 ml), in the other

three beakers we placed 100 ml of water and added

(25%, 50%, 100%) of blackberry pulp, respectively) as

shown in Fig. 7. To verify the functionality of the ap-

plication, tests were performed in which a user used the

application to take measurements as shown in (Fig. 8).

4.1 Data collected

The data collected by the designed application were

pH [H+] and Temperature [ C] measured in blackberry

pulp at diﬀerent concentrations. (Fig. 9) shows the data

recorded by the application for pH and temperature.

17 International Journal of Engineering Insights, (2023) 1:1

Fig. 8 Use of the Application

Fig. 9 Measurement of pH [H+] and Temperature [ C]

4.2 Analysis of the experiments

The data obtained were plotted through Excel, the ex-

periment was performed four times so that there is

greater reliability in the data, these were measured for

four hours in total, the measurement was carried out

ﬁrst by measuring the pH in water for four minutes,

then the sensor probe was transferred to the glass con-

taining the 25% solution for four minutes, the pH probe

is returned to water for another four minutes, this pro-

cedure is performed with the 50% and 100% solutions.

(Fig. 10) shows the graphs obtained from the four ex-

periments.

Table 2 shows the pH variations in the four experi-

ments carried out; the pH variation in experiment 1 is

2.48% between the 25% to 50% dilutions and 0.66% in

the 50% to 100% dilution. In experiment 2 is 1.87% be-

tween the 25% to 50% dilutions and 0.97% in the 50%

to 100% dilution. In experiment 3, the variation in the

25% to 50% dilutions is 1.27%, and the variation in the

50% to 100% dilutions is 1.63%. Finally, in experiment

4, the variation between the 25% to 50% dilutions is

1.27%, and the variation in the 50% to 100% dilution is

1.62%, which allows determining that the sensor works

correctly due to high repeatability even though diﬀerent

reference levels. For example, in experiment 4, the wa-

ter was mixed with blackberry pulp due to the changes

made from the sensor probe to the diﬀerent beaker.

Table 2 Data Analysis

Concentration [%] pH Mean [H+] Variation [H+]

Experiment 1 25 3.22 0.08

50 3.05 0.02

100 3.02

Experiment 2 25 3.21 0.06

50 3.08 0.03

100 3.02

Experiment 3 25 3.15 0.04

50 3.06 0.05

100 2.96

Experiment 4 25 3.15 0.04

50 3.08 0.05

100 2.99

5 Conclusions

The system assembled for this experiment has two func-

tions that allow on the one hand to monitor the pH

and temperature, and on the other to control the mixer

of the environment where the system is installed. The

measurements can be observed in real time through the

application designed in App Inventor, the data were

stored in the Thingspeak platform and then exported

to Excel to make graphs and make decisions regard-

ing the behavior of the pH, which allows to know if

the blackberry pulp has the necessary conditions to be

consumed. In addition, it allowed to analyze the acid-

ity level of the blackberry with diﬀerent concentration

levels. As future work, it is recommended that diﬀer-

ent environments be used to monitor pH behavior, and

to determine which is the most suitable for preserving

blackberry pulp over time.

Acknowledgements Special thanks to CICHE Research Cen-

ter and SISAu Research Group of the Universidad Indoam´erica

for the support in this research. The results of this work are

part of the project “Education 4.0 applied to the teaching of

skills STEAM”. This work was supported in part by collabo-

ration with the REDTPI4.0 CYTED program.

Conﬂict of interest

The authors declare that they have no conﬂict of inter-

est.

18 International Journal of Engineering Insights, (2023) 1:1

Fig. 10 pH data of the diﬀerent blackberry dilutions by experiment

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