Eng. Proc., 2023, JIEE 2023

This report presents the development of a robotic arm for the efficient packaging of chocolates in a small-scale process. The robotic arm has a PRR (prismatic–rotational–rotational) configuration and uses a universal vacuum grip (UVG) to manipulate the chocolates with precision. Various materials and components were used, such as 3D-printed PLA parts for the mechanical elements and flexible TPU bands for optimal movement control. In terms of electronics, NEMA motors, an Arduino board, and a CNC interface were used for the precise control of the motors. The programming was conducted in Python and a graphical user interface (GUI) was created to manage the sequence of movements of the robotic arm. Key parameters, such as the accuracy in the placement of the chocolates, the grip strength, and the shape recovery ability were evaluated. The results demonstrate the successful integration of the robotic arm in the packaging process, achieving an efficient and consistent placement of the chocolates in the plastic trays. This project highlights the importance and potential of automation in the food packaging industry, by improving productivity, reducing human error, and ensuring packaging quality. The knowledge and results obtained in this project contribute to the field of robotics. Full article

The proposed work offers a concise review of the application of machine learning (ML) to cellular network handovers (HO) via the Systematic Mapping Study (SMS) methodology, emphasizing the problem areas and requirements. The key points include the paramount role of high-quality data, with meticulous data acquisition and preprocessing as vital steps in ML dataset construction. The article identifies prevalent parameters for HO enhancement and underscores the diversity of ML algorithms, aligning them with specific data input and tasks. This study establishes a robust basis for forthcoming research in applying machine learning to cellular network HOs. Full article

In today’s world, the integration of renewable energies is essential to meet the surging global energy demand and reduce pollution. Ecuador, with its favorable geographical location, boasts abundant renewable resources. Currently, the country has large-scale renewable energy projects such as “El Aromo” in Manabí, led by Solarpack, and Villonaco in Loja, with its wind power plant. In this study, Homer Pro software is used to simulate two microgrids with solar and wind energy in the mentioned sectors, allowing us to conduct comprehensive economic and energy analyses to determine the most viable configurations. Full article

In the ever-evolving construction industry, the incorporation of the Industrial Internet of Things (IIoT) through Low-power Wireless Area Networks (LPWAN), such as LoRaWAN, has emerged as a practical solution for addressing the challenges posed by the limited 5G cellular coverage found in solutions like NB-IoT and LTE-M, especially when deployed in remote locations. Open-source LPWAN platforms like The Things Network (TTN) and ChirpStack have played a pivotal role in fostering the adoption of LoRa technology by providing a mature and cost-effective ecosystem that facilitates efficient device resource management. Within this context, maintaining continuous surveillance of LPWAN network gateways becomes critically important, requiring a meticulous examination of status indicators and an evaluation of the communication quality. This paper introduces a structured approach for extracting data from TTN to create a comprehensive gateway monitoring system. The methodology encompasses various aspects, including ensuring seamless server connectivity, specifically focusing on efficient information management and integration of real-world construction data. This foundational work sets the stage for a more in-depth exploration of the diverse management components within the network ecosystem. Full article

As the penetration level of solar power generation increases in smart cities and microgrids, an automatic energy management system (EMS) without human supervision is most communly deployed. Therefore, assuring safe and reliable data against cyber attacks such as false data injection attacks (FDIAs) has become of utmost importance. To address the aforementioned problem, this paper proposes detecting FDIAs considering visual data. The aim of visual state estimation is to enhance the resilience and security of renewable energy systems. This approach provides an additional layer of defense against cyber attacks, ensuring the integrity and reliability of solar power generation data and facilitating the efficient and secure operation of EMS. The proposed approach uses a modified VGG-16 neural network model to obtain an intermediate representation that provides textual and numerical explanations about the visual weather conditions from sky images. Numerical results and simulations corroborate the validity of our proposed approach. The performance of the modified VGG-16 neural network model is also compared with previous state-of-the-art machine learning models in terms of accuracy. Full article

A problem with applying machine learning for analyzing power system dynamics is the lack of specific datasets. In this realm, defining a strong methodology to obtain power system dynamic data is an important task prior to the application of any machine learning tool. This is particularly important considering the current growing research in the field of self-healing grids. Thus, this paper presents a well-defined stochastic methodology that can be used to generate dynamic data that can afterwards be analyzed using machine learning tools. The proposed method is based on a Monte Carlo simulation and this paper presents the procedure to perform it. Full article

The modernization of the current electric power grid into a smart grid requires the integration of advanced instrumentation, automation, and communication technologies to optimize efficiency, safety, and reliability. In traditional power grids, communication and control tasks are concentrated in substations, limiting their coverage to high-power equipment. As distributed energy resources increase in different sections of the grid, power flow becomes bi-directional. This requires monitoring and control at the Transmission and Distribution (T&D) level, which forms the largest portion of the power grid. To achieve efficient energy flow management and enable consumer participation in demand management, the integration of information and communication technologies (ICTs) is essential. Wireless sensor networks (WSNs) have been identified as a suitable solution for communications within the distribution network. An ongoing challenge, however, is the definition of the best candidates to solve this problem, among the currently available wireless technologies. This paper reviews different wireless communication technologies that provide robustness, reliability, speed, scalability, and cost-effectiveness for monitoring distribution lines. An outline of the architecture for smart grid communications, the definition of sensor network requirements for power line environments, and an overview of specific studies focusing on technology comparisons are the main contributions of this paper. The purpose of this review is to delineate current technologies in order to establish potential future research directions within the field. Full article

An Electric Power System (EPS) is a dynamic system that, due to continuous variations in the load, the presence of disturbances, switching operations, and/or the operation of the protection system, is never in a steady state. A deficit in generation causes a drop in the system’s frequency that, if not controlled, could result in the loss of synchronism between generators or areas and, in the worst-case scenario, a total or partial system collapse. This article presents a methodology to identify a subset of representative events that generalizes the N-1 generation contingency space; this subset can later be applied in the development of Under-Frequency Load-Shedding (UFLS) schemes based on the Rate of Change of Frequency (ROCOF). Full article

This paper shows the implementation and performance analysis of motion control algorithms for a 3D Concrete Printing system based on an industrial robotic arm. This work is part of the project of digital fabrication of low-cost housing. Regarding the technological architecture integrated in the present work, the hardware devices used are the EPSON C12 industrial robot arm and the RC700-A controller, and the software tools are Fusion 360 and RC+. To evaluate the point extraction and sequencing algorithms of a 3D structure and the motion control algorithms of the robot arm, three test wall models were designed: a semi-circle with horizontal undulations, a semi-circle with vertical undulations and an orthohedron without undulations. For the performance analysis, 140 trajectory times were extracted for each test model. The extracted values are the trajectory time intervals of the wall model envelope for each layer and of the internal trajectory of the wall model infill. Due to the increasing and decreasing trends of time for specific cases, it was concluded that in the working area of the robot arm, there are parts in which the robot is more efficient and therefore the joints offer less inertia for certain types of movements, for example straight or curved movements and short or long movements. Full article

This article presents the implementation and the evaluation of a transmission–reception system for Physical Downlink Control Channel (PDCCH) within the context of fifth-generation cellular networks (5G/NR). The research focuses on characterizing the behavior of the PDCCH channel concerning different User Equipment (UE) positions through simulations conducted in MATLAB. Two scenarios are considered: a lossless system and a system with losses, where the outcomes are presented in terms of Bit Error Rate (BER) vs. Signal to Noise Ratio (SNR) and BER vs. Transmit Power, respectively. One contribution of the paper is the explanation transmission–reception system for PDCCH in MATLAB, while the second contribution is the presentation of simulation results. From results, it was deduced that higher UE height corresponds to improved channel performance, greater UE elevation angle leads to enhanced channel performance, and increased carrier frequency results in reduced performance of the physical control PDCCH channel. Full article

An improved ring resonator structure consisting of a capacitive coupling fixture is presented. Dielectric characterization is carried out using a fitting method that allows for comparison between measured and simulated results by setting a coupling level of about −4 dB and an unloaded quality factor of about 54. The key factor in this approach is the coupled energy, which permits measurements to be made well above the noise threshold. Furthermore, when applied within a frequency range, the dielectric dispersion can be studied as well. As proof-of-concept fixtures, five structures for the L-band at resonance frequencies of 1 GHz, 1.25 GHz, 1.5 GHz, 1.75 GHz, and 2 GHz are designed, manufactured, and measured. The method applied in this study provides good results as verified by error calculations. Full article

Industrial robots are used in a variety of industrial process tasks, and due to the complexity of the environment in which these systems are deployed, more robust and accurate control methods are required. Deep reinforcement learning emerges as a comprehensive approach that directly allows for the mapping of sensor data and the setting of motion actions to the robot. In this work, we propose a robotic system implemented in a semi-photorealistic simulator whose motion control is based on the A2C algorithm in a DRL agent; the task to be performed is to reach a goal within a work area. The evaluation is executed in a simulation scenario where a fixed position of a target is maintained while the agent (robotic manipulator) tries to reach it with the end-effector from an initial position. Finally, the trained agent fulfills the established task; this is demonstrated by the results obtained in the training and evaluation processes, and the reward value increases when the measured distance decreases between the end-effector and the target. Full article

In the rapidly evolving landscape of cancer drug research, cellular lines serve as invaluable tools for understanding drug-sensitive and drug-resistant tumors. The computational representation of cellular lines is usually based on genomic profiling, even though this method cannot be applied in a large scale. This study introduces a novel approach to the computational representation of cellular lines using text mining techniques. By meticulously extracting and analyzing textual data from the scientific literature, we developed a computational representation of these cellular lines. Our methodology encompassed advanced Natural Language Processing (NLP) for text extraction and machine learning models for predictive analysis. We achieved a comprehensive description of each cellular line. To validate our findings, we generated a distance matrix for all cellular lines, leading to the construction of a dendrogram representing cellular line relationships. This dendrogram shows a resemblance with the established cell line ontology from CLO. Our results bridge the gap between cellular line representation and text mining, offering a robust computational model that can significantly impact cancer drug research. Full article

This research article presents a comprehensive study focusing on advancing radar systems for unmanned aerial vehicle (UAV) surveillance in cluttered environments. The proliferation of UAV technology and its diverse applications have raised concerns about airspace security. To tackle this issue, this article introduces a novel simulator designed to evaluate the performance of primary monopulse radar processors. The simulator accurately replicates scenarios involving clutter Weibull distributions, stationary and moving targets, as well as pulse compression situations, thereby enabling precise and controlled evaluations. The study employs the simulator to assess radar processors, including a variant of moving target detection (MTD) and a constant false alarm rate (CFAR) processor. By implementing a rigorous methodology, the article underscores the significance of simulating cluttered conditions in refining the effectiveness of radar processors. The results yield valuable insights, facilitating objective interpretations. The proposed simulator and its implications contribute to enhancing UAV surveillance and airspace security, thereby pushing forward the capabilities of radar systems. Full article

Decentralized generation has gained importance in the energy industry, since self-consumption with renewable resources presents attractive costs and allows load management actions. In this sense, photovoltaic generation systems are a promising technology. This work presents a proposal for a peak shaving system using solar photovoltaic (PV) energy and a battery storage system, known as battery energy storage systems (BESS), to be installed by an industrial customer to reduce energy consumption during peak hours. For the study, a hybrid approach is presented, starting from deterministic variables, such as the demand curve of the industry under study, and the generation of stochastic variables, such as the energy production of the photovoltaic system. For the analysis of the proposed peak shaving system, the design and sizing of the photovoltaic systems are developed in a base case of self-generation and an optimized system for the system to cover the energy demand generated during peak hours. The technical–economic study carried out in the research allowed us to determine the optimal power of the photovoltaic system with the storage system. The proposed system allows the integration of a peak shaving strategy from a certain power limit, in order to cover the peak demand over this power limit, allowing the system to be profitable under the current regulations and standards in Ecuador. Full article

With emerging technologies like cloud computing and big data, managing traditional networks has become more demanding. Software-defined networking (SDN) promises faster implementation, flexibility, and simplified network management. However, due to SDN’s centralized nature, it encounters limitations. SDN controllers should have enough processing power to deal with a high amount of flow. In addition, a single point of failure may affect the network’s resiliency. For these issues, multi-instance implementation enables distributed control. However, this solution implies an intrinsic controller-to-controller synchronization channel. In this article, we propose different failure scenarios in both the data and control planes to provide network administrators with a clear view of the constraints of network reliability, load balancing, and scalability in SDN environments. The simulation results show that, regarding resiliency, SDN networks require half the time compared to traditional networks in order to recover from a link failure. Regarding load-balancing capabilities, load balancing is not guaranteed with the reactive forwarding approach (on-demand flow installation). Lastly, the SDN multi-instance solution impacts the network performance by between 1% and 21% compared to the single-instance case. Full article

The significance of electric vehicles is progressively escalating, underscoring the criticality of technologies underpinning the functionality of their propulsion systems. This particular case study delves into the simulation of field-oriented control, coupled with field weakening, aimed at regulating a salient-pole permanent-magnet synchronous motor (PMSM). This approach involves the utilization of two cascaded loops for current and voltage, each employing PI controllers. The fine-tuning of these controllers’ parameters hinges on the motor characteristics, as well as the desired response bandwidth. Full article

This paper introduces the design and fabrication of a versatile capacitor bank developed specifically for its integration within the innovative flash joule heating (FJH) technique, aimed at synthesizing graphene. The capacitor bank offers two adaptable configurations, providing options for capacitance at 180,000 µF and 68,000 µF, combined with a maximum charging capability of 400 V. This equipment facilitates the swift conversion of carbon-containing materials into graphene by harnessing transient current discharges. The proposed capacitor bank facilitates the execution of comprehensive research pertaining to graphene production from diverse carbon sources, opening an opportunity for advancing exploration within this rapidly evolving field of study in Ecuador. Full article

This paper presents an overview of the findings in the handover (HO) process performance within three routes in Quito, Ecuador. We used the Net-Monitor Software to gather information from one of the three national mobile operators. Then, we used the R tool to analyze the HO performance. We analyze several performance metrics, such as HO types, HO conditions, and the ping-pong process. Analysis of the results of the outdoor drive tests demonstrate that the radio frequency (RF) parameters, such as Received Signal Strength Indicator (RSSI), Reference Signal Received Quality (RSRQ), power margin, times radio frequency measurements repeats, and HO percentage to nearest BS, are extremely important during different HO types and ping-pong processes because there are statistical differences in these measured RF parameters. The main measurement results demonstrate that RSSI difference between inter HO and intra HO is 20 dB, whereas HOs are performed when the mobile device (MS) gets farther from the base station (BS), approximately 50% of total HOs. Operator achieves a high ping-pong rate of approximately 10% of total HOs. Full article

Standardization and collaborative integration are fundamental for the implementation of Industry 4.0. The Open Communication Platform Unified Architecture (OPC UA) standard plays a crucial role in communication by enabling the development of heterogeneous systems and facilitating the seamless exchange of data between devices. To take full advantage of OPC UA’s capabilities, it is necessary to unlock other application services, such as cloud computing. By having more tools at their disposal, industries can increase their efficiency and optimize data-driven decision making. In this study, it was proposed to use OPC UA standard in a Client/Server model to leverage OPC UA paradigms along with Software Development Kits (SDKs). The development was carried out using Python as the programming language, both to host the server on a Raspberry Pi 4B and to set up the client on a Personal Computer (PC). This client will centralize the data for sending to the Clever Cloud logging platforms and for web visualization on Tago.IO. The interoperability problem of communicating between two platforms with different Operating Systems (OS) was addressed by integrating the OPC UA standard. The configured interval of 10 s recorded an average of 11.11 s, with a maximum timeout of 59 s for data-logging temperature, pressure, humidity, and altitude. The client proved to be Hypertext Transfer Protocol Secure (HTTPS) compliant, allowing connection to Web platforms. Full article

Ecuador may face an accelerated energy transition in the next 15 years due to the reduction of its oil reserves, affecting industries that require oil derivatives. To achieve a transition toward renewable energy without affecting the industry, this research proposed a technoeconomic evaluation of a hybrid system with solar flat plate collectors and photovoltaic modules that drive an absorption chiller and a compression chiller. The system supplies heat, cooling, and electricity to the winemaking industry in Ecuador. The best results for the hybrid systems reached a levelized cost of energy (LCOEn) of 0.171 USD/kWh and 0.157 USD/kWh in Guayaquil and Quito, respectively. For both locations, the LCOEn for the hybrid systems represents a decrease of the LCOEn of 53% and 32% concerning the individual solar photovoltaic and solar thermal systems, respectively. Therefore, the proposed hybrid system has a significant potential to integrate solar energy into the industry sector. Full article

This article presents the development of a prototype software for a terrestrial digital TV signal spectrum analyzer using software-defined radio (SDR). This study involves four phases: signal reception from Quito’s TV channels, configuring the software and hardware to work within the 470–698 MHz frequency range using the One-seg service of the ISDB-Tb standard, setting up the spectrum analyzer with a low-pass filter to reduce noise, and analyzing the results by visualizing digital TV signals from various areas of Quito with the SMPlayer software. While capturing TDT signals in Ecuador, it was discovered that some channels’ signals lacked playable audiovisual content on video players during testing. Full article

This paper discusses the innovative application of a new methodology for acquiring load curves in energy systems such as Azogues Electric Company (EEA). The proposed approach imports the database from Excel and, through an iterative clustering algorithm based on density with noise, generates daily load curves with a breakdown of weekdays and weekends, identifying one curve by type of consumer. Moreover, the groups obtained are validated by means of a Silhouette verification index (IS) identifying bad groupings, which are discarded to obtain results. Per unit value responses are presented through tables with hourly values on weekdays and weekends. The graphical comparison with the previous methodology of real measurements in Excel is also added. Full article

This work presents an overview of fifth-generation (5G) technology, its key functionalities, and its applications. Then, we introduce the topic of 5G radio network planning, making analysis and design methods for coverage and capacity determinations, considering 3GPP standards. With these results, we apply the standards and procedures for a business/dense urban area in Quito city, considering the relevant parameters for calculations and simulations using the Atoll tool. Specifically, we consider the following: the key propagation models Macro/Micro, bandwidths, use cases, data rates, frequency bands (3.5/28 GHz), and modulation orders, etc. Finally, we discuss the proposed network planning and provide some useful insights regarding the 5G mobile network in Quito. Full article