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Real-Time Urban Animal Monitoring Using Transfer Learning-Based Object Detection on Web Platforms
(MDPI AG, 2026-05-13)
Fierro Silva, Carlos Julio
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Sánchez, Carlos A.
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Sánchez, Jorge S.
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Del-Valle-Soto, Carolina
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Velasco, Nancy
This study addresses the growing need for scalable solutions to monitor domestic and stray animals in urban environments. The objective is to develop and evaluate a real-time animal detection system using transfer learning and lightweight object detection models. The methodology includes the adaptation of a custom dataset with annotated images of cats and dogs under real-world conditions, followed by preprocessing, data augmentation, and model fine-tuning. Two architectures, SSD-MobileNet and YOLOv26s, were trained and evaluated using standard metrics such as precision, recall, F1-score, and mAP, as well as operational indicators like inference speed and system responsiveness. The best-performing model was integrated into a web-based platform with real-time detection, mobile access, and automated alerts. Results show that YOLOv26s outperforms SSD-MobileNet, achieving higher precision and recall while significantly reducing false positives and improving background discrimination. The system demonstrates near real-time performance suitable for monitoring applications and effective deployment across different input sources. The discussion findings highlight that integrating detection models with notification and visualization tools enhances practical applicability. Although SSD-MobileNet is suitable for low-resource environments, YOLOv26s provides a better balance between accuracy and reliability, making it more appropriate for real-world intelligent monitoring systems
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ROS2-Based Low-Cost Mobile Robot for Educational Assistance with Reactive Navigation and Semantic-Cached Language Processing
(MDPI AG, 2026-07-08)
Aucapiña, Sebastián Alexis
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Benalcázar, Nataly Cecilia
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Varela Aldas, José
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Isa-Jara, Ramiro
Educational environments, particularly those with limited resources, require affordable mobile robots capable of combining human–robot interaction, autonomous assistance, and academic support without continuous dependence on cloud services. This work presents a low-cost ROS2-based mobile robot implemented on a Raspberry Pi 4B to provide educational assistance in Spanish within controlled classroom environments. The system integrates voice interaction, text-to-speech synthesis, YOLOv8n-based object perception, a specialized door detection model, ultrasonic and inertial sensing, differential-drive control, and a hybrid natural language processing architecture based on semantic caching, local inference, and optional cloud connectivity. Two task-dependent operating modes, education and navigation, selectively activate ROS2 nodes to reduce computational load and energy consumption. Experimental tests conducted in a university classroom evaluated speech recognition, vision models, natural language processing alternatives, sensor behavior, and battery life. The speech recognition module achieved 98% accuracy under both quiet and noisy conditions. YOLOv8n achieved an F1-score of 0.975 for common classroom objects, while the specialized door detector achieved 100% recall with 58.7% precision. The semantic cache correctly resolved recurrent academic queries in the exact-match evaluation, with an average latency of 3.8 s, reducing the need for external language models in known-question scenarios. The robot operated for 96 min in education mode and 75.6 min in navigation mode. These results demonstrate that Spanish voice interaction, reactive navigation, academic question answering, and resource-aware operation can be integrated into a single low-cost edge robotic platform for educational environments. © 2026 by the authors.
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Point Mass Planning and NMPC Tracking for Time-Optimal Agile Quadrotor Gate Navigation
(Institute of Electrical and Electronics Engineers (IEEE), 2026)
Guevara, Bryan S.
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Brandao, Alexandre Santos
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Varela Aldas, José
Time-optimal agile flight through a sequence of three-dimensional gates requires a consistent coupling between trajectory planning and tracking control. Point-mass planners offer fast numerical solutions for free-final-time optimisation, but the value of progressively enriching the reference fed to a nonlinear model predictive control (nmpc) tracker through a differential flatness bridge has not been clearly characterised on multi-gate circuits. This paper presents a modular three-stage pipeline: an offline time-optimal point-mass model (pmm) planner solved with CasADi and IPOPT; a differential flatness bridge that maps the flat outputs and their time derivatives to a full quadrotor reference comprising desired position, velocity, attitude quaternion, body angular rate, and collective thrust; and a body-rate nmpc tracker implemented on the acados SQP-RTI scheme with an SO(3) logarithmic-map external cost. Two reference configurations are compared in a software-in-the-loop setup that drives the MuJoCo physics engine through ROS 2 under a randomly seeded external-force disturbance. The baseline, nmpc-Att, uses only a yaw-only attitude reference derived from the velocity heading and carries no angular-rate or thrust feedforward. The proposed configuration, nmpc-Full, activates the complete flat reference, including the full attitude quaternion, body angular rate, and thrust feedforward. Results on a seven-gate figure-8 and an eight-gate vertical loop show that reference enrichment yields a categorical improvement in gate crossing and a systematic reduction of tracking error without increasing solver cost. The loop circuit further highlights a structural limitation of the common practice yaw-only reference: it cannot represent inverted attitudes, and only the flatness-based reference resolves this case
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Fiber–matrix interaction governs compressive strength in agave-bagasse-reinforced adobe: a factorial experiment with two-way ANOVA and competing mechanism analysis
(Frontiers Media SA, 2026-07-31)
De-Obaldia-Escalante, Marcela
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Del-Valle-Soto, Carolina
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Acevedo-Parra, H. R.
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Montoya-Márquez, Orlando
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Varela Aldas, José
Natural-fiber reinforcement is widely cited as a pathway to improve the mechanical performance of adobe, but reported effects on compressive strength are inconsistent across studies: some find improvement, others find degradation, and the choice of experimental conditions rarely disentangles the role of the fiber from that of the matrix. This study quantifies the coupling through a balanced factorial experiment. Forty-nine adobe specimens of (Formula presented) cm were manufactured with three granular compositions (sand-dominated, jal-dominated, and balanced, where jal is a regional non-plastic silt of Jalisco, Mexico) and four mass fractions of agave-bagasse fiber (0%, 0.5%, 1%, and 2%), and were tested under Mexican standard NMX-C-036-ONNCCE by an accredited external laboratory. Three complementary analytical tools are applied to the resulting dataset: (i) a two-way analysis of variance (ANOVA), (ii) a reinforcement efficiency index (Formula presented) with bootstrap confidence intervals, and (iii) a competing mechanism phenomenological descriptor (Formula presented) that separates a saturating reinforcement term from a linear disruption term. The two-way ANOVA reveals a highly significant mixture–fiber interaction ((Formula presented), (Formula presented), and partial (Formula presented)), which is stronger than either main effect and statistically demonstrates that the sign of the fiber effect is not an intrinsic property of the fiber but rather a property of the fiber–matrix pair. For sand-containing mixtures, the reinforcement efficiency index is (Formula presented) [M1, 95% bootstrap CI (0.96, 1.32)] and (Formula presented) [M3, (0.92, 1.59)] at the optimum (Formula presented); a non-parametric bootstrap over 5, 000 resamples places the optimum at (Formula presented) with posterior probability (Formula presented) (M1) and (Formula presented) (M3). For the jal-dominated mixture, fiber inclusion is net destructive [(Formula presented), (0.68, 0.95) at (Formula presented)], with Welch (Formula presented)-tests rejecting equivalence with the control at (Formula presented) (0.5%) and (Formula presented) (2%) and Cohen’s effect sizes (Formula presented). The best-performing conditions yield mean compressive strengths of 3.22 MPa, which exceeds the 2.0 MPa minimum required by NMX-C-441-ONNCCE-2011 for non-structural masonry by 60%. An immersion test shows that unstabilized specimens disintegrate within 2–3 min, bounding applications to non-exposed or externally protected uses and defining the primary direction for future work.
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Multipath Routing Protocol: For Wireless Ad-hoc Networks Based on Fibonacci
(Zarqa University, 2026-07-04)
Sun, Haiyun
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Varela Aldas, José
A WANET, which stands for Wireless Ad hoc Network, is a temporary network in which nodes are connected to each other via wireless links and there is no central management. Due to its adaptive structure, WANET is very useful in situations when quick communication link setup is necessary. On the other hand, Channel Contention (CC), degrades the performance of WANET and is a major contributor to packet drops. To solve the CC problem, this paper proposes a routing protocol called Multipath Channel Contention Based Routing (MCCBR). Using MCCBR, several paths are discovered for data transmission that have minimal contention between the source and destination. Then the packets are distributed over the discovered routes based on the Fibonacci sequence. The process of searching for new paths for transmission is initiated when the number of found paths becomes less than 50%. The proposed routing protocol was tested and verified using NS2 simulator. The performance of MCCBR was evaluated against the Ad hoc On Demand Distance Vector (AODV) and Channel Contention Based Routing (CCBR) protocols. MCCBR outperformed AODV and CCBR in terms of Packet Delivery Ratio (PDR), End-to-End (E2E) delay, and normalized Media Access Control (MAC) overhead. © 2026, Zarka Private University. All rights reserved.
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Experimental and data-driven evaluation of transport-layer and application-layer security for MQTT-based IoT networks
(Elsevier BV, 2026-12)
Del-Valle-Soto, Carolina
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Alvarez-Garcia, Maria Fernanda
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Valdivia, Leonardo J.
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Del-Puerto-Flores, José A.
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Varela Aldas, José
The rapid expansion of Internet of Things (IoT) deployments has intensified the need for secure and efficient communication mechanisms tailored to resource-constrained devices. Message Queuing Telemetry Transport (MQTT) is widely adopted due to its lightweight design; however, it lacks native security support, requiring external protection mechanisms that may significantly affect system performance. This paper presents a comprehensive experimental and data-driven evaluation of two security paradigms for MQTT-based IoT networks implemented on ESP32 microcontrollers: transport-layer security using TLS and application-layer encryption based on elliptic curve cryptography (ECC) for key exchange combined with AES symmetric encryption. The analysis jointly evaluates memory utilization, end-to-end latency, energy consumption, and resistance to passive traffic interception under identical experimental conditions. In addition to conventional metric-based comparisons, multivariate statistical analysis and unsupervised learning techniques are employed as exploratory tools to characterize the system-level behavior induced by each security scheme. Results show that Transport Layer Security (TLS) offers stronger confidentiality guarantees at the cost of higher memory overhead, while the ECC–(Advanced Encryption Standard) AES approach significantly reduces memory footprint with moderate latency penalties and comparable energy consumption. Multivariate analysis further reveals that each security mechanism induces a distinct performance regime, providing a compact joint characterization of the security–performance trade-offs across the evaluated configurations.
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Immersive AR–ROS 2 Teleoperation Architecture for a Physical Quadruped Robot
(MDPI AG, 2026-07-15)
Criollo, Erick
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Oñate, William
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Caiza, Gustavo
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Andaluz, Víctor
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Varela Aldas, José
Immersive teleoperation of quadruped robots requires the operator to interpret a remote environment, make decisions, and maintain control over a dynamic platform through mediated visual feedback and networked command transmission. This study presents and validates a reproducible augmented reality (AR)–ROS 2 architecture designed to analyze the relationship between system-level technical conditions and operator experience during immersive teleoperation of a physical quadruped robot. The system integrates Meta Quest 3, Unity, UDP communication, ROS 2 middleware, and Xiaomi CyberDog within a modular workflow that jointly supports immersive control, live RGB/depth perception, physical robot execution, and user-centered HRI evaluation. The architecture decouples command transmission and visual feedback into two UDP-based channels: the control channel maps virtual joysticks and discrete HUD buttons to ROS 2 locomotion and action commands, while the perception channel transmits compressed RGB and depth frames for display in the AR interface. Under nominal conditions, the control channel achieved a mean end-to-end latency of 9.37 ms, a P95 of 18.45 ms, an effective update frequency close to 18 Hz, and 100% packet reception. Compared with ROS-TCP-Endpoint, the proposed UDP bridge showed similar latency but higher flow integrity, avoiding duplicate, parsing, and dropped-command events. The visual channel achieved mean end-to-end latencies of 21.09 ms for RGB and 26.99 ms for depth, with frame reception rates of 91.78% and 91.10%, respectively, under a shared 18.67 Mbps mobile network. A complementary network degradation analysis showed that the control channel remained operational under bandwidth reduction, packet loss, added latency, combined degradation, and physical separation of the robot. The user evaluation with 25 participants yielded a corrected Raw NASA-TLX score of (Formula presented.), a positive perceived performance score of (Formula presented.), and a System Usability Scale score of (Formula presented.), indicating low perceived workload and high usability. These results show that low end-to-end latency, high flow integrity, and stable visual feedback were accompanied by low perceived workload and high usability, indicating that the technical temporal response, stability, and robustness of the communication channels are consistent with an effective and low-demand operator experience during AR-based teleoperation of a physical quadruped robot.
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Does the use of dedicated mobile devices in magnetism classes improve student learning?
(Frontiers Media SA, 2026-04-21)
Varela Aldas, José
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Collay, Washington
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Del-Valle-Soto, Carolina
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Palacios-Navarro, Guillermo
Mobile devices have been evaluated from multiple perspectives as tools to support classroom learning; however, devices specifically dedicated to learning activities still require further research to elucidate their influence in the classroom. This study aimed to evaluate whether the use of dedicated mobile devices for teaching basic magnetism content improves learning among secondary school students. A quantitative, comparative quasi-experimental study with non-equivalent groups was conducted ((Formula presented)) with secondary school students in Ecuador. The experimental group used an educational application running on a dedicated mobile device (M5Stack Core2) and interacted with an electromagnet as a didactic peripheral, whereas the control group received a traditional teacher-centered lesson supported by slides. Learning outcomes were measured using a teacher-designed theoretical test administered at the end of a 90-min session. Mean scores were similar between groups (experimental: 7.32; control: 7.58). After verifying assumptions of normality and homogeneity of variance, an independent-samples t-test showed no statistically significant differences ((Formula presented)), and the effect size was small (Cohen’s (Formula presented)). Under the conditions evaluated, the dedicated mobile device did not produce measurable gains in knowledge performance compared to the traditional lesson. Longer interventions, larger samples, and longitudinal study designs are needed to clarify when and how this technology may provide educational benefits.
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Hybrid BLE–LoRa architectures for energy-efficient and resilient wireless sensor networks: Experimental validation and adaptive clustering strategies
(Springer Science and Business Media LLC, 2026-06-03)
Del-Valle-Soto, Carolina
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Briseño, Ramon A.
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Valdivia, Leonardo J.
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Varela Aldas, José
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Visconti, Paolo
Wireless Sensor Networks are increasingly deployed in mission-critical scenarios where resilience and energy efficiency are paramount. This paper presents a hybrid architecture combining Bluetooth Low Energy (BLE) and Long Range (LoRa) technologies to enhance both robustness and energy-aware performance in adversarial environments characterized by reactive jamming attacks. A comprehensive experimental testbed was developed, integrating BLE and LoRa nodes, a dual-protocol gateway, and a reactive jammer emulator. We introduce an adaptive clustering algorithm that performs energy-aware role assignment and jamming mitigation based on signal anomaly detection and multi-metric routing. To validate its effectiveness, we conducted an extensive time-series analysis on energy consumption, retransmission rates, and signal resilience under both mitigated and non-mitigated conditions across BLE-only, LoRa-only, and hybrid BLE-LoRa networks. The results show protocol-dependent performance trade-offs under the proposed mitigation algorithm. While LoRa-only and hybrid BLE–LoRa networks exhibit consistent reductions in energy consumption, retransmissions, and variability, the BLE-only configuration demonstrates improved resilience at the cost of a moderate increase in energy usage and retransmission activity due to clustering and control overhead. Notably, the BLE-LoRa architecture balances delivery assurance and energy efficiency while maintaining communication even under interference. Furthermore, we provide statistical modeling and hypothesis testing confirming the mitigation algorithm’s significant impact. These findings offer a critical empirical contribution to the design of resilient and energy-aware heterogeneous WSNs and demonstrate the viability of real-time adaptive mitigation strategies for emerging smart environments
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A hybrid bio-inspired visual servoing strategy for aerial grasping of static and moving targets
(2026)
Carvajal, Christian
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Víctor H. Andaluz
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Flavio Roberti
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Varela Aldas, José
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Ricardo Carelli
This article presents a bio-inspired visual servo control scheme for aerial grasping of static and moving targets using aerial manipulators (AM). The proposed approach is based on a cascaded control architecture. The first control layer implements a bio-inspired hybrid visual servo strategy that combines Image Based Visual Servoing (IBVS) and Position Based Visual Servoing (PBVS), motivated by the prey capturing behavior of birds of prey. An Aerial-Eye-to-Hand visual configuration is introduced, in which an onboard camera mounted on the aerial platform is used to simultaneously regulate image plane features and spatial variables associated with the target. The grasping task is organized into four autonomous stages, enabling coordinated detection, approach, grasping, and transportation. Exploiting the redundancy of aerial manipulators, the proposed scheme allows the simultaneous fulfillment of multiple control objectives, including target visibility maintenance and accurate end effector positioning. The second control layer consists of a dynamic compensation controller formulated in terms of reference velocities, which facilitates its implementation on aerial platforms with embedded low level controllers. A formal stability and robustness analysis of the cascaded closed-loop system is provided. Experimental results, including real-world aerial grasping of moving ground targets in unstructured environments, demonstrate the effectiveness of the proposed approach. © 2026 The Author(s)
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