][]  
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/  
© 2026 by authors.  
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 [6]. 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 [14].  
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  
[
4
]. Identifying solutions that maximize energy efficiency while maintaining communication quality becomes  
essential.  
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.  
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-  
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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 [11]. Additionally, the  
scalability and effectiveness of LoRaWAN for multiple IoT applications have been demonstrated, highlighting  
its long-range transmission capabilities [12].  
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 [8].  
In industrial contexts, a hybrid LoRa and NB-IoT system has been proposed for vibration synchroniza-  
tion in critical machinery [  
also been analyzed [13].  
5]. 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 [10] 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 [  
7
].  
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 [9], [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  
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  
     
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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  
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.  
   
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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.  
•
•
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  
30  
30  
30  
30  
30  
30  
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  
24  
24  
24  
24  
24  
9.6  
9.6  
9.6  
9.6  
9.6  
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  
30  
30  
30  
30  
27  
27  
28  
27  
28  
10  
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  
100  
100  
30  
30  
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.