][]

Research article

Implementation of LoRa Technology to Improve Data

Transmission Reliability in Energy Monitoring

Applications

Implementación de tecnología LoRa para mejorar la

ﬁabilidad de la transmisión de datos en aplicaciones de

monitoreo energético

Andrés Lowis Torregroza¹

1

Faculty of Engineering, Universidad de la Costa, Barranquilla, 080002, Colombia; alowis@cuc.edu.co

∗

Correspondence: alowis@cuc.edu.co

Citation: Lowis, A. Implementation of LoRa Technology to Improve Data Transmission Reliability in Energy Monitoring Applications.

OnBoard Knowledge Journal 2025, 1, 7. https://doi.org/10.70554/OBJK2025.v01n01.08

Received: 14/03/2025, Accepted: 29/03/2025, Published: 16/05/2025

DOI: https://doi.org/10.70554/OBJK2025.v01n01.08

Abstract: Intelligent energy monitoring using IoT systems has become increasingly important in both industrial and

domestic environments due to its ability to optimize energy consumption and generate signiﬁcant savings. This paper

presents the design and development of a technology based on IoT and LoRa communication, aimed at measuring and

transmitting energy consumption data for the company e2 Energía Eﬁciente. A low-power wide-area network (LPWAN)

communication system was implemented, evaluating its performance under different environmental and operating

conditions. Key variables such as energy consumption, transmission speed and stability, and data security were analyzed.

Tests carried out in real environments, with various obstacles and distances, validated the effectiveness of the system in

terms of coverage, reliability, and usefulness for the collection and analysis of energy data.

Keywords: Communication; Data transmission; Energy monitoring; Internet of Things; LPWAN

Resumen: El monitoreo inteligente de energía mediante sistemas IoT ha adquirido creciente relevancia tanto en

entornos industriales como domésticos, debido a su capacidad para optimizar el consumo energético y generar ahorros

signiﬁcativos. En este trabajo se presenta el diseño y desarrollo de una tecnología basada en IoT y comunicación

LoRa, orientada a la medición y transmisión de datos de consumo energético para la empresa e2 Energía Eﬁciente. Se

implementó un sistema de comunicación de red de área amplia y baja potencia (LPWAN), evaluando su desempeño bajo

diferentes condiciones ambientales y operativas. Se analizaron variables clave como el consumo energético, la velocidad y

estabilidad en la transmisión, así como la seguridad de los datos. Las pruebas realizadas en entornos reales, con diversos

obstáculos y distancias, permitieron validar la efectividad del sistema en términos de cobertura, ﬁabilidad y utilidad para

la recolección y análisis de datos energéticos.

Palabras clave: Comunicación; Internet de las cosas; LPWAN; Monitoreo de energía; Transmisión de datos

OnBoard Knowledge Journal 2025, 1, 7.

https://revistasescuelanaval.com/obk/

Licensed by Escuela Naval de Cadetes "Almirante Padilla", COL.

This article is freely accessible and distributed under the terms and conditions

of Creative Commons Attribution (https://creativecommons.org/licenses/by/4.0/).

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1. Introdution

In a context of accelerated technological progress and growing environmental awareness, energy efﬁ-

ciency has become a fundamental pillar for the sustainability and competitiveness of industrial systems. The

ability to monitor and manage energy consumption in real time, particularly in remote settings, enables re-

source optimization, cost reduction, and mitigation of environmental impacts. Solutions based on the Internet

of Things (IoT) and wireless communications have emerged as key tools to address these challenges; however,

their implementation faces limitations in environments characterized by physical obstacles, interference, and

long transmission distances.

LoRa (Long Range) technology offers an efﬁcient alternative for wireless data transmission in energy

monitoring applications due to its low power consumption and extended communication range. This study

focuses on the design and implementation of an IoT-based monitoring system using LoRa communication,

applied to a Chiller-type air conditioning system in an industrial facility. The main objective is to ensure

reliable data transmission between the Chiller room and the control room, separated by a distance of 120

meters, under real operating conditions.

The work includes experimental tests to evaluate system performance under different scenarios, ranging

from line-of-sight transmissions to environments with signiﬁcant physical obstacles. Key variables such as

data transmission rate, packet loss, latency, and link stability are analyzed, along with the integration of

environmental sensors to enrich the transmitted data payload. The results make it possible to determine the

optimal conﬁguration of LoRa modules to ensure efﬁcient and continuous monitoring, thereby laying the

groundwork for more effective energy management.

Real-time wireless data transmission in industrial environments presents signiﬁcant challenges due to

the physical and operational conditions of production facilities. Factors such as electromagnetic interference,

physical obstacles, adverse atmospheric conditions, and long distances between transmitters and receivers

can degrade the reliability of wireless links [7]. As a result, the lack of critical real-time information may

affect system status monitoring, thereby compromising decision-making processes and operational efﬁciency.

In industrial plants, sensors monitor variables such as temperature, pressure, humidity, ﬂow, and liquid

levels. However, transmitting these data to a centralized system can be hindered by physical infrastructure

limitations, long distances, and environmental conditions [2]. Choosing an appropriate wireless technology

is therefore essential. Solutions such as Wi-Fi, ZigBee, Bluetooth, and LoRa offer different advantages and

limitations in range, energy consumption, cost, security, and interference resistance [15].

Long-distance communication also increases challenges related to energy consumption, especially for

LPWAN devices that must operate autonomously for extended periods without continuous power availability

[

5

]. Identifying solutions that maximize energy efﬁciency while maintaining communication quality becomes

essential.

Previous works have also addressed energy consumption monitoring from the perspective of user-

oriented savings and household energy management. For instance, a consumption monitoring device

based on embedded computing was proposed to estimate household energy use and support more rational

electricity consumption, highlighting the relevance of accessible monitoring systems for promoting energy

efﬁciency [4].

For the company e2 Energía Eﬁciente, one of the main challenges is the inconsistency in data acquisition

from monitoring systems and sensors, which affects statistical reporting, energy assessments, maintenance

decisions, and anomaly detection. These limitations reduce system reliability and the ability to validate

energy-saving measures over time.

For this reason, this research aims to minimize data loss through a LoRa-based wireless communication

infrastructure characterized by low power consumption and long communication range. The objective is

to ensure continuous and reliable energy data transmission, enabling accurate analysis, rapid operational

response, and improved overall energy management.

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The structure of this article is organized as follows: Section 2 presents the main contributions of this

research. Section 3 reviews relevant studies and technological approaches related to industrial wireless

monitoring systems. Section 4 explains the motivation and context underlying the implementation of the

LoRa-based solution. Section 5 describes the methodological approach, system architecture, and experimental

procedures. Section 6 presents the results obtained from testing the system under different scenarios, includ-

ing transmission range, packet loss, latency, and system performance in real operating conditions. Finally,

Section 7 summarizes the ﬁndings and outlines opportunities for future improvements and applications.

2. Contributions

This paper presents the following main contributions:

i.

The design and characterization of an IoT-based LoRa communication architecture aimed at improving

the reliability of data transmission in energy monitoring applications.

ii.

iii.

The implementation of a low-power wireless monitoring system tailored to real industrial operating

conditions, integrating environmental and energy-related sensors.

An experimental evaluation of the proposed architecture under both line-of-sight and non-line-of-

sight scenarios, analyzing key communication metrics such as packet loss, transmission rate, latency,

and link stability.

iv.

The identiﬁcation of optimal LoRa conﬁguration parameters that balance energy efﬁciency and

communication reliability in industrial environments.

3. Related Works

The implementation of low-power wireless technologies for data monitoring in industrial environments

has been addressed from multiple perspectives. A LoRa-based smart lighting system has been developed

to improve energy efﬁciency through automatic adjustment of lighting intensity [12]. Additionally, the

scalability and effectiveness of LoRaWAN for multiple IoT applications have been demonstrated, highlighting

its long-range transmission capabilities [13].

Sigfox technology has also been employed in remote monitoring systems. Its implementation has proven

effective for capturing pressure and humidity data in tailings dams, emphasizing its low energy consumption

[

3]. Furthermore, an ESP32-based system has been designed to evaluate solar collectors, underscoring

accessible and efﬁcient solutions for renewable energy environments [9].

In industrial contexts, a hybrid LoRa and NB-IoT system has been proposed for vibration synchroniza-

tion in critical machinery [

also been analyzed [14].

6]. Conversely, energy optimization strategies in Wi-Fi–based IoT devices have

Speciﬁc applications in rural or remote sectors have likewise adopted these technologies, such as the

implementation of LoRaWAN for wind turbine monitoring [11] and the integration of LoRa in unmanned

aerial vehicles (UAVs) for data acquisition in inaccessible areas [2]. Moreover, the performance of LoRaWAN

in smart agriculture has been evaluated, highlighting its reliability in scenarios with limited connectivity [

8

].

Finally, improvements in communication protocols for low-power devices have been proposed, prior-

itizing energy efﬁciency, data compression, and scalability—critical aspects in LPWAN networks such as

Sigfox and LoRaWAN [10], [1].

4. Justiﬁcation

The increase in energy costs and the growing demand for sustainability have driven the adoption of

technological solutions that enable efﬁcient energy consumption management, particularly in industrial

environments. Air conditioning systems, which are essential to ensure optimal production and storage

conditions, represent one of the largest sources of energy consumption. The absence of real-time monitoring

limits the ability to respond promptly to failures or inefﬁciencies, thereby hindering performance optimization

and energy savings.

In this context, the implementation of an IoT-based monitoring system using LoRa technology constitutes

a low-power, long-range solution capable of overcoming the physical and connectivity barriers commonly

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found in industrial facilities. This project is oriented toward the design of a prototype that enables real-time

acquisition, transmission, and visualization of energy-related data, thereby supporting informed decision-

making and continuous improvement of the monitored systems.

Moreover, the proposed approach offers ﬂexibility and scalability, making it applicable not only to

industrial environments but also to residential settings. The adaptable system architecture allows replication

and expansion for future applications focused on sustainability and energy resource optimization, establishing

it as a key tool for modern energy management strategies.

5. Methodology

This study is framed as applied research focused on technological development, with the objective

of implementing a long-range wireless communication network for monitoring energy consumption in an

industrial Chiller-type air conditioning system. To this end, low-cost devices based on LoRa technology are

employed, enabling an accessible, replicable, and scalable solution for future projects.

The study seeks to establish the relationship between the characteristics of the industrial environment

and the performance of the wireless communication in terms of communication range, latency, packet loss,

and energy consumption. The project is structured into sequential phases, including system design, hardware

and ﬁrmware implementation, transmission testing under controlled and real operating conditions, and

analysis of the collected data to validate the effectiveness of the proposed system.

5.1. System Architecture

The design of the proposed system follows a structured architecture in which different functional blocks

are integrated to enable efﬁcient and continuous data transmission for subsequent monitoring and analysis.

This architecture is described in Table 1 and illustrated in Figure 1.

Figure 1. System structure.

Source: The authors.

5.2. Experimental Procedures

To evaluate the performance of the LoRa-based communication system, a set of experimental tests

was developed to analyze data transmission rate, packet loss, effective communication range, and energy

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Table 1. System architecture blocks and their corresponding descriptions.

Block

Description

This block is mainly composed of measurement and data

acquisition instruments. Temperature and humidity sen-

sors are used for the air conditioning system. In addition,

an energy meter is incorporated to obtain system power

values, enabling comprehensive energy monitoring.

This block includes the data transmission device (trans-

mitter node), which uses an ESP8266 microcontroller for

the sequential execution, storage, and packaging of data

obtained from the sensor unit. It also integrates a LoRa

module responsible for transmitting data packets over

long distances to the receiver device.

This block corresponds to the device responsible for re-

ceiving the data packets sent by the transmitter. The

receiver node consists of a Raspberry Pi, which processes

the received data and uploads them to a cloud-based

database. An additional LoRa module is used to receive

the transmitted packets, conﬁgured identically to the

transmitter module to establish a direct communication

link.

Sensor unit

Data transmission

Data reception

At this stage, the received data stored in the database are

visualized through a monitoring platform hosted on the

Raspberry Pi, conﬁgured to operate as a server. This setup

enables real-time monitoring as well as historical data

analysis, allowing comprehensive system monitoring.

This block is essential for the operation of all other system

components. It is responsible for supplying the required

voltage to each device, as energy consumption is nec-

essary for transmitting and receiving data packets over

long distances, even when using low-power wide-area

network (LPWAN) devices.

Data analysis and visualization

Energy management

Source: The authors.

consumption. These tests were conducted prior to the ﬁnal installation of the system and included the

optimization of LoRa module parameters at both the transmitter and receiver nodes.

The experimental evaluation was structured into three sequential phases:

•

Phase 1: The performance of data transmission was evaluated under ideal conditions, with direct

line-of-sight and no physical obstacles, in order to determine the maximum communication range

between the nodes.

Phase 2: Tests were carried out within the real application environment, varying the distance between

devices and exposing the communication link to electromagnetic interference and materials that affect

signal propagation.

Phase 3: The total packet transmission was measured at the ﬁnal installation site, an industrial warehouse

with multiple physical obstacles, simulating the system’s ﬁnal operational scenario.

5.2.1. Maximum Distance Test Between Transmitter and Receiver Nodes

The ﬁrst experimental phase evaluated the maximum communication range between the LoRa modules

under ideal line-of-sight conditions, with no physical obstacles and outside the application environment. The

test was conducted along a section of the Malecón del Río (Barranquilla), covering a progressive distance

from 0 to 1120 meters, increased in intervals of 160 meters, as illustrated in Figure 2. Beyond this distance,

visual obstructions were detected that affected the communication link.

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Figure 2. Location of each interval separated every 160 meters of distance.

Source: Google Earth.

The slave node transmitted periodic signals consisting of LED activation commands to the master node,

which conﬁrmed successful reception through synchronized activation of its own LED. For each evaluated

distance, 30 packets were transmitted using different transmission rate (AirRate) conﬁgurations, ranging

from 1.2 kbps to 19.2 kbps, while maintaining a ﬁxed transmission power of 30 dBm.

For each distance and conﬁguration combination, the number of successfully received packets was

recorded, allowing the calculation of the packet loss percentage. The test locations were georeferenced using

GPS coordinates, which are summarized in table 2.

Table 2. Parameters of the maximum distance test between transmitter and receiver nodes under line-of-sight conditions.

Test No.

Latitude

11.0111188

11.0100551

11.0090652

11.0080818

11.0070761

11.0060598

11.0050119

11.0040272

Longitude

-74.7834366

-74.7824335

-74.7813659

-74.7802944

-74.7792591

-74.7782130

-74.7772045

11.0040272

Distance (m) No. of Packets

1

2

3

4

5

6

7

8

0

30

160

320

480

640

800

960

1120

Source: The authors.

5.2.2. Data Transmission Test Within the Application Environment with Distance Variation

The second experimental phase focused on evaluating the performance of the transmission system

within the real application environment, speciﬁcally inside the company’s facilities where the Chiller-type air

conditioning system is in operation. Unlike the ﬁrst phase, this test was conducted under non-line-of-sight

conditions between the nodes, exposing the LoRa link to physical obstacles, electromagnetic interference,

and human activity (Figure 3).

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Figure 3. Location of the receiving node at different points within the company environment.

Source: Google Earth.

An SHT30 sensor was used to transmit temperature and humidity data, thereby increasing the size of

the transmission packet. The tests began in the Chiller room (0 m) and progressed in intervals of 20 meters up

to a maximum distance of 100 meters, which was limited by the dimensions of the industrial facility (Figure

4).

Figure 4. Distance between each location point of the receiving node within the company environment.

Source: Google Maps.

The initial conﬁguration of the LoRa modules consisted of a transmission power of 24 dBm and a

data rate (AirRate) of 9.6 kbps, selected based on the results obtained in Phase 1 and the trade-off between

energy consumption and transmission speed. However, when packet loss exceeded 10%, the transmission

parameters were adjusted by increasing the transmission power or reducing the data rate as required.

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During this phase, the packet loss percentage was quantiﬁed, and the transmission delay between

packet emission and reception was measured. For the calculation of the average latency, lost packets were

excluded, allowing for a more accurate assessment of the link performance (Table 3).

Table 3. Initial parameters of the transmission test with distance variation within the application environment.

Test No.

Latitude

11.022655

11.022498

11.022965

11.023147

11.023173

11.023049

Longitude

-74.802791

-74.802696

-74.802668

-74.802539

-74.802361

-74.801997

DNRT (m) IP (dBm) IR (kbps)

1

2

3

4

5

6

0

20

40

60

80

100

24

9.6

Note: DNRT = Distance between receiver and transmitter nodes; IP = Initial transmission power; IR = Initial data rate. Source: The

authors.

5.2.3. Total Data Transmission Test at the Node Installation Site

The third and ﬁnal phase consisted of evaluating the system in its deﬁnitive operational environment.

The LoRa devices were installed at the locations deﬁned in the project: the transmitter node in the Chiller

room, responsible for acquiring energy system data, and the receiver node in the control room, separated

by approximately 120 meters and characterized by multiple physical obstacles typical of an industrial

environment (Figure 5).

Figure 5. Location of the receiver node within the control room.

Source: The authors.

This test focused on determining the optimal conﬁguration of transmission parameters, such as trans-

mission power and data rate (AirRate), in order to achieve a balance between energy efﬁciency and commu-

nication quality. The average packet loss percentage and transmission delay were monitored, considering a

ﬁxed data transmission interval of 20 seconds, which is suitable for continuous energy monitoring.

The ﬁnal selected conﬁguration was required to ensure low energy consumption, minimal packet loss,

and low latency. The results obtained from this evaluation are presented in detail in the following section.

6. Results

6.1. Development of PCB Boards for Data Acquisition and Transmission

As part of the development of the LoRa-based energy monitoring system, dedicated printed circuit

boards (PCBs) were designed and implemented to integrate the microcontroller with the communication

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modules and data acquisition sensors. This approach ensured an organized, efﬁcient, and reliable intercon-

nection among components, avoiding the use of temporary wired connections that could compromise system

stability.

The PCB design process was carried out using EasyEDA Pro software, which facilitated circuit routing

and veriﬁcation. Two types of boards were developed:

•

Interface board for the LoRa E32 module: Designed to enable communication between the LoRa module

and the microcontroller, ensuring electrical compatibility and appropriate physical connectivity for data

transmission and reception (see Figure 6).

•

Data acquisition and transmission board: Responsible for managing the acquisition of temperature

and humidity data from the SHT30 sensor and transmitting data packets to the receiver node. This

board includes the necessary connections for power supply, I2C communication with the sensor, and

integration with the LoRa module (see Figure 7).

Figure 6. PCB design and actual image of the LoRa module board.

Source: The authors.

Figure 7. PCB design and actual image of the sensor and data acquisition card.

Source: The authors.

6.2. LoRa Module Conﬁguration

For wireless communication between the transmitter and receiver nodes, the LoRa E32 module was used

and conﬁgured according to the parameters permitted for operation in Colombia. The selected operating

frequency was 433 MHz, in compliance with the regulations of the Agencia Nacional del Espectro (ANE),

within the range established by the LoRa Alliance (433–434.79 MHz for the region).

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The communication channel conﬁguration was kept constant between both nodes to ensure synchro-

nization and to avoid interference from external devices. Additionally, unique addresses were assigned to

each module within the same channel to enable clear and unidirectional identiﬁcation during transmission,

ensuring that messages were delivered exclusively to the intended destination node (Figure 8).

Figure 8. Conﬁguration diagram for the transmitter and receiver nodes.

Source: The authors.

6.3. Analysis of Transmitted and Received Packets

In the evaluation of communication under direct line-of-sight conditions, it was observed that the link

between the transmitter and receiver nodes maintained acceptable performance up to a distance of 640

meters, as shown in Figure 9, provided that the transmission rate did not exceed 9.6 kbps. Beyond this

distance, and particularly under conﬁgurations with higher data rates, a signiﬁcant increase in packet loss

was observed. This behavior indicates that, to ensure link reliability at longer distances, it is necessary to

reduce the transmission rate, thereby enabling a more robust modulation that is more tolerant to signal

attenuation.

Figure 9 illustrates the behavior of the packet loss percentage as a function of distance and the different

transmission rate conﬁgurations, allowing the identiﬁcation of optimal parameters for efﬁcient communica-

tion under ideal conditions.

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Figure 9. Percentage of packets lost by distance in meters and transmission rate conﬁguration of the LoRa modules.

Source: The authors.

Based on the previous ﬁgure, it can be observed that the lower the transmission rate, the lower the packet

loss percentage. Therefore, for the proposed monitoring system, it is necessary to establish a moderately high

transmission rate that does not signiﬁcantly increase packet losses, since each received data packet is critical

for accurate real-time monitoring.

It is important to note that a packet loss percentage of 10% or lower was considered acceptable, given

the high frequency of data transmission. Based on this criterion, an analysis of the effective communication

range as a function of the transmission rate was performed for both modules.

6.4. Effective Range by Transmission Rate

The maximum distance between nodes with a packet loss percentage equal to or lower than 10%

is considered the effective communication range, taking into account the transmission rate suitable for

line-of-sight communication between both points.

Considering the results presented in table 4, it can be determined that at shorter distances between

nodes, signiﬁcantly higher transmission rates can be achieved. Consequently, this parameter was taken into

account for the development of subsequent experimental tests.

Table 4. Effective communication range by transmission rate in the test area.

AirRate (kbps) Effective Range (m) SP RP PL (%)

19.2

9.6

4.8

2.4

1.2

160

640

800

1120

1200

30

27

28

27

28

10

7

10

7

Note: AirRate = Transmission rate; SP = Sent packets; RP = Received packets; PL = Packet loss.

Source: The authors.

6.5. Packet Loss as a Function of Transmission Distance

The LoRa link was initially conﬁgured with a transmission rate of 9.6 kbps and a transmission power of

24 dBm. Under these conditions, tests were conducted at ﬁxed time intervals of 20 seconds, collecting a total

of 30 data samples for each evaluated distance.

The analysis focused on determining the packet loss percentage as a function of the transmission

distance. The obtained results show a gradual increase in data loss as the separation between nodes increases,

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highlighting the limitations of the initial conﬁguration in non-line-of-sight environments. Figure 10 presents

the detailed behavior of the packet loss percentage for each tested distance.

Figure 10. Percentage of packet loss by transmission distance, with initial conﬁguration of 24 dBm at 9.6 kbps of the LoRa

module.

Source: The authors.

The ﬁgure 10 indicates that the packet loss percentage remains below 10% up to a distance of 80 meters

between both nodes under non-line-of-sight conditions. At a distance of 100 meters, a signiﬁcant increase in

packet loss is observed, reaching approximately 70% of data not received. The successfully received data

under these conditions are shown in ﬁgure 11.

Figure 11. Percentage of packet loss by transmission distance, with initial conﬁguration of 24 dBm at 9.6 kbps of the LoRa

module.

Source: The authors.

One of the strategies proposed to improve the packet loss percentage at a node separation distance

of 100 meters involved testing different conﬁgurations of the LoRa modules, with the aim of analyzing the

effectiveness of data transmission.

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6.6. Transmission Effectiveness

By increasing the transmission power and reducing the data rate, the effective communication range

was signiﬁcantly extended, even in the presence of environmental obstacles. Based on this approach, the

results of transmitted and received packets under this optimized conﬁguration were obtained, maintaining

minimal changes with respect to the initial parameter values used in this test. These results are presented in

Figure 12.

Figure 12. Number of packets sent and received for each conﬁguration made to the LoRa modules with transmission

distance of 100 meters.

Source: The authors.

From the aforementioned ﬁgure, the number of received packets for each conﬁguration applied to

the LoRa modules can be determined. Consequently, the transmission effectiveness percentage for each

conﬁguration was calculated, as shown in table 5.

Table 5. Transmission effectiveness percentage by conﬁguration of the LoRa modules.

Distance (m) Sent Packets Received Packets TE (%)

Conﬁguration

24 dBm / 9.6 kbps

27 dBm / 9.6 kbps

27 dBm / 4.8 kbps

100

30

9

25

29

30.00

83.33

96.67

Source: The authors.

Ultimately, a high transmission effectiveness was achieved using a transmission power of 27 dBm and a

data rate of 4.8 kbps on both LoRa modules.

6.7. Packet Transmission Delay

Although reducing the transmission rate to 4.8 kbps improves signal penetration in environments with

physical obstacles, it also results in an increase in the response time between nodes. This effect was observed

when comparing data reception times at the Raspberry Pi, which were higher than those obtained with a

transmission rate of 9.6 kbps.

To quantify this difference, a comparative analysis of transmission delay was conducted for each

conﬁgured data rate, while keeping the transmission power and the distance between nodes constant. For

this purpose, 30 packets were transmitted per data rate, with a ﬁxed interval of 20 seconds between packets,

and the average delay was calculated for each case. The results of this analysis are presented in Figure 13,

where the relationship between reduced transmission speed and increased latency is clearly illustrated.

Based on the ﬁgure 13, a transmission power of 27 dBm combined with a data rate of 4.8 kbps was

selected as the optimal conﬁguration for the LoRa modules. This conﬁguration maintains an acceptable delay

for real-time data monitoring.

The temperature and humidity data obtained using this conﬁguration are shown in the ﬁgure 14.

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Figure 13. Delay time per transmission rate in the module conﬁguration.

Source: The authors.

Figure 14. Capture of ambient temperature and humidity data, with a total of 29 packets received out of 30 transmitted.

Transmission effectiveness of 96.67%.

Source: The authors.

6.8. Results of the Transmission Test at the Node Installation Location

In the ﬁnal test, the receiver node was installed in the control room, located 120 meters from the

transmitter node, which remained in the Chiller room. Under this scenario, system performance was

evaluated by transmitting environmental data (temperature and humidity) from the transmitter node to the

receiver using the optimal conﬁguration obtained from previous tests.

During the test, a total of 30 packets were transmitted, of which 26 were successfully received, rep-

resenting a packet loss of 13.33%. This result provides a realistic reference for the performance of LoRa

communication under industrial operating conditions, where multiple physical obstacles and sources of

interference are present. Figure 15 summarizes the data collected during this phase and illustrates the system

behavior in the ﬁnal installation environment.

Due to the relatively low transmission effectiveness observed during the initial communication between

the Chiller room and the control room, the transmission rate was reduced to 2.4 kbps. Although this

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Figure 15. Captures temperature and humidity data at a distance of 120 meters within the application environment.

Transmission effectiveness of 86.67%.

Source: The authors.

adjustment increased the transmission delay, the increase did not signiﬁcantly affect the 20-second sampling

interval established for continuous monitoring. On the contrary, this change substantially improved link

performance, achieving 100% effectiveness in packet reception.

This result highlights the advantage of dynamically adapting the transmission rate to optimize com-

munication in environments with physical obstacles and electromagnetic noise. Figure 16 presents the data

collected under this conﬁguration.

Figure 16. Captures temperature and humidity data up to 120 meters away within the application environment. 100%

transmission effectiveness.

Source: The authors.

7. Conclusions

Based on the results obtained from the experimental tests conducted in each phase and the implemen-

tation of the LoRa modules, it can be concluded that high reliability was achieved in data transmission for

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real-time energy monitoring applications. This performance is attributed to the appropriate conﬁguration

and efﬁcient operation of the LoRa modules, which resulted in high transmission effectiveness and a nearly

negligible packet loss rate. Additionally, successful data acquisition was achieved through the integration

of sensors and energy measurement equipment, with the collected data packaged and transmitted to the

receiver node for storage and visualization within the monitoring system.

The initial experimental tests made it possible to determine the maximum effective communication

range under line-of-sight conditions as a function of the conﬁgured transmission rate for each LoRa device.

These results demonstrate that reliable data transmission can be achieved over long distances in open

environments, while also conﬁrming that data transmission in non-line-of-sight scenarios is feasible when

appropriate transmission rate conﬁgurations are applied to the LoRa modules.

In addition to effective communication range, key performance metrics such as transmission effec-

tiveness and packet loss percentages were obtained based on a deﬁned number of transmitted packets,

supported by instrumentation and sensors that provide quantitative values for data analysis within speciﬁc

time intervals. These metrics offer a comprehensive assessment of the communication link performance

under varying environmental conditions.

The results also indicate that antenna placement plays a critical role in communication quality. Locating

node antennas at elevated positions and in open spaces can signiﬁcantly reduce transmission interference

caused by environmental factors such as the presence of other antennas or concrete structures, thereby

improving overall system performance.

The design of the data acquisition board combined with the ESP8266 microcontroller enables the

integration of digital sensors for various monitoring applications, particularly those requiring temperature

measurements. However, the system architecture allows for further enhancements, such as the development

of acquisition boards capable of supporting additional sensor types and extended functionalities.

Regarding data management, the use of a database enables real-time visualization and analysis of the

monitored variables, as well as historical data analysis of system behavior. Furthermore, this architecture

allows access to the monitoring platform from any device connected to the same local area network as the

Raspberry Pi hosting the database.

Finally, this development provides a ﬂexible foundation for future improvements, including remote

access to the database through cloud-based servers to enable monitoring from any location, the implementa-

tion of local data storage with automatic synchronization in the event of network failures, the expansion of

the system to support a larger number of sensors and measurement devices through enhanced acquisition

hardware, and the incorporation of control variables and automated alert mechanisms to enable a more

comprehensive system analysis and improved operational performance.

Author Contributions: Andrés Lowis Torregroza: Conceptualization, Methodology, Software, Validation, Formal

analysis, Investigation, Resources, Data curation, Writing – original draft, Writing – review & editing, Visualization,

Supervision, Project administration, Funding acquisition.

The author has read and agreed to the published version of the manuscript. Please refer to the CRediT taxonomy for the

deﬁnitions of the terms.

Funding: This research received no external funding.

Institutional Review Board Statement: Not applicable, since the present study does not involvehuman personnel or

animals.

Informed Consent Statement: This study is limited to the use of technological resources, so nohuman personnel or

animals are involved.

Conﬂicts of Interest: Under the authorship of this research, it is declared that there is no conﬂict of interest with the

present research.

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Authors’ Biography

Andrés Lowis Torregroza Electronic Engineer with a professional focus on engineering ap-

plications and data analysis. I am recognized for strong communication skills, teamwork,

problem-solving abilities, adaptability, creativity, and effective time management. I have

approximately four years of experience in data analysis roles, working primarily with tech-

nologies such as Python, SQL, and Power BI, as well as machine learning models, DevOps

practices, process automation and optimization, and PCB circuit design and development.

Disclaimer/Editor’s Note: Statements, opinions, and data contained in all publications are solely those of the individual

authors and contributors and not of the OnBoard Knowledge Journal and/or the editor(s), disclaiming any responsibility

for any injury to persons or property resulting from any ideas, methods, instructions, or products referred to in the

content.