Real-time Communication Research Articles

Solar-Powered GSM Irrigation for Intelligent Water Management

Efficient water management is crucial for sustainable agriculture and landscaping. This project introduces a novel solution, combining solar power and GSM technology to create an intelligent irrigation system. Integrated GSM connectivity enables remote monitoring and control, allowing users to adjust irrigation schedules and settings from anywhere, enhancing convenience and flexibility. By leveraging data analytics and sensor feedback, the system optimizes water usage, ensuring precise delivery based on plant needs and environmental conditions. This approach not only conserves water but also promotes healthier plant growth and higher yields. The integration of GSM technology ensures real-time communication and alerts, allowing users to respond promptly to changing conditions and unforeseen events. Through case studies and performance evaluations, the presentation will demonstrate the system's reliability, durability, and cost- effectiveness, underscoring its viability for widespread adoption. Attendees will gain insights into how solar- powered GSM irrigation can revolutionize water management practices, empower farmers and gardeners, and contribute to building resilient, sustainable ecosystems in a rapidly changing world.

Activated carbon and their nanocomposites derived from vegetable and fruit residues for water treatment

Water pollution remains a pressing environmental issue, with diverse pollutants such as heavy metals, pharmaceuticals, dyes, and aromatic hydrocarbon compounds posing a significant threat to clean water access. Historically, biomass-derived activated carbons (ACs) have served as effective adsorbents for water treatment, owing to their inherent porosity and expansive surface area. Nanocomposites have emerged as a means to enhance the absorption properties of ACs, surpassing conventional AC performance. Biomass-based activated carbon nanocomposites (ACNCs) hold promise due to their high surface area and cost-effectiveness. This review explores recent advancements in biomass-based ACNCs, emphasizing their remarkable adsorption efficiencies and paving the way for future research in developing efficient and affordable ACNCs. Leveraging real-time communication for ACNC applications presents a viable approach to addressing cost concerns.

A Cyber–Physical System Based on Digital Twin and 3D SCADA for Real-Time Monitoring of Olive Oil Mills

Cyber–physical systems involve the creation, continuous updating, and monitoring of virtual replicas that closely mirror their physical counterparts. These virtual representations are fed by real-time data from sensors, Internet of Things (IoT) devices, and other sources, enabling a dynamic and accurate reflection of the state of the physical system. This emphasizes the importance of data synchronization, visualization, and interaction within virtual environments as a means to improve decision-making, training, maintenance, and overall operational efficiency. This paper presents a novel approach to a cyber–physical system that integrates virtual reality (VR)-based digital twins and 3D SCADA in the context of Industry 4.0 for the monitoring and optimization of an olive mill. The methodology leverages virtual reality to create a digital twin that enables immersive data-driven simulations for olive mill monitoring. The proposed CPS takes data from the physical environment through the existing sensors and measurement elements in the olive mill, concentrates them, and exposes them to the virtual environment through the Open Platform Communication United Architecture (OPC-UA) protocol, thus establishing bidirectional and real-time communication. Furthermore, in the proposed virtual environment, the digital twin is interfaced with the 3D SCADA system, allowing it to create virtual models of the process. This innovative approach has the potential to revolutionize the olive oil industry by improving operational efficiency, product quality, and sustainability while optimizing maintenance practices.

Railway Train Collision Avoidance on Same track and Animal Detection Using AI - IoT

The increasing demand for safer and more efficient railway transportation systems has prompted the exploration of advanced technologies to mitigate collision risks and address emerging challenges such as animal incursions on railway tracks. This paper proposes a comprehensive solution leveraging Artificial Intelligence (AI) and Internet of Things (IoT) technologies for real-time detection and avoidance of collisions between trains operating on the same track and encounters with animals. These sensors capture various environmental and operational data such as train positions, velocities, and track conditions. The AI algorithms analyze this data to identify potential collision risks and animal intrusions. Additionally, real-time communication between trains and the centralized control system enables timely intervention and rerouting decisions to ensure safe operations. The system incorporates advanced image recognition algorithms to detect and classify animals near railway tracks. Utilizing high-resolution cameras and IoT-connected devices, the system identifies animals in the vicinity and alerts train operators or initiates automated braking mechanisms to prevent accidents caused by animal incursions. Key features of the proposed system include scalability to accommodate varying railway infrastructures, adaptability to diverse environmental conditions, and interoperability with existing railway signaling and control systems. Moreover, the integration of AI and IoT technologies enhances the system's predictive capabilities, enabling proactive risk mitigation and improving overall.

Safety Helmet for Miners

Abstract: The safety helmets basically aim at safety of miners reducing the risks of accidents. It also highlights the hazardous environments of mining and potential dangers that the workers face while working in mines. Safety helmets will be containing infrared sensors which keep track of the environment of the miner. It highlights the inherent risks miners face, including poor visibility, potential collisions, and hazardous conditions. The helmets are capable of alerting the miners from dangers. Infrared sensors can sense the heat signatures and obstacles in real-time resulting in spatial awareness. The helmets also consist of Arduino to enable real-time data processing and communication integration. The helmet also consists of LoRa which provide wireless communication between helmets and receiver ends, which would notify them in case of any emergency. The abstract concludes by enhancing the importance of IR-sensors, LoRa and Arduino which interfaces all of the above equipment.

Telehealth Monitoring System for Chronic Disease Management

This project introduces a carefully crafted remote health monitoring solution to support chronic illness management in response to the changing healthcare environment. The use of cutting-edge microcontroller technology, the foundation of this all-inclusive solution, is at the core of this breakthrough. Because of the system's ability to operate beyond regional boundaries, users can manage chronic illnesses proactively. The approach promises real-time data capture and communication by seamlessly integrating microcontrollers into the monitoring process, enabling patients and healthcare practitioners alike. This project is a paradigm shift in healthcare, utilizing technology to provide continuous, tailored, and accessible monitoring for improved health and better chronic illness management.

An IoT- based Measure Guage for Surveil of Water Quality by Parametric Quantity

Abstract: The document highlights the pressing need to address water-related challenges through innovative approaches, particularly by integrating IoT technology for water quality monitoring. Emphasizing the critical importance of safe drinking water, it proposes an IoT-based framework for continuous water quality assessment. This framework utilizes specific sensors to measure key parameters like turbidity, pH, and temperature, with microcontrollers processing the data for transmission to an Arduino Uno board. Real-time communication enables timely sharing of crucial information with stakeholders, facilitating proactive water resource management. The system determines water drinkability based on compiled data and provides a visual representation for easy interpretation by non-experts. Overall, the integration of IoT offers a comprehensive solution, ensuring safe water consumption and community engagement in water quality management, essential for securing sustainable water resources.

Intelligent Traffic Light Control System

Abstract: The "Intelligent traffic light control system " project introduces an innovative approach to traffic management, aiming to expedite emergency vehicle passage. Utilizing Zigbee and Radio-Frequency Identification (RFID) technology, this system assigns a unique RFID tag to each vehicle, enabling precise tracking and control at traffic junctions. The scenarios involving emergency vehicle clearance, the system's responsiveness shines. When an emergency vehicle clearance approaches, the system rapidly receives the signal from zigbee transmitter associated with it and promptly triggers a green signal at the traffic junction. This prioritization ensures that emergency vehicles can navigate the traffic with minimal delays, potentially saving lives. Another remarkable feature of the system is stolen vehicle detection capability. In the event that a vehicle with a specific RFID tag is reported as stolen, the system is programmed to take action. It sends immediate SMS notifications to relevant authorities, such as law enforcement or the vehicle owner. This proactive response enhances the chances of recovering stolen vehicles and contributes to overall security. The hardware components of this system include Arduino Uno. Arduino Uno serves as the central control unit, processing RFID data and executing signal adjustments, while the GSM module facilitates real-time communication, enabling SMS alerts and notifications. The " Intelligent traffic light control system " project exemplifies how RFID technology and zigbee technology can revolutionize traffic management. By incorporating data analysis and automation, this system offers a multifaceted solution to common traffic-related challenges.

Agri Cart

Abstract: "AGRI CART" is a revolutionary platform designed to modernize agricultural practices, connecting farmers directly with consumers through an online marketplace. This innovative system eliminates middlemen, empowering farmers to sell their produce at fair prices while enabling consumers to access fresh, locally sourced goods. Through AGRI CART, farmers can showcase their products, manage inventory, and set competitive prices, enhancing their profitability and sustainability. Consumers benefit from a diverse range of high-quality, farm-fresh produce delivered conveniently to their doorstep. The platform also fosters transparency, allowing consumers to trace the origin of their food and learn about the farmers who cultivate it. AGRI CART prioritizes environmental sustainability by promoting organic farming practices and reducing food waste. With user-friendly interfaces and secure payment options, the platform ensures a seamless experience for both farmers and consumers. Furthermore, AGRI CART supports rural development by creating opportunities for small-scale farmers to reach broader markets and improve their livelihoods. Through its mobile application, AGRI CART facilitates real-time communication between farmers and consumers, fostering community engagement and trust. By bridging the gap between producers and consumers, AGRI CART revolutionizes the agricultural supply chain, promoting fairness, transparency, and sustainability in food production and distribution.

Smart Home Warning System Using ESP- 32 Cam

Abstract: Smart home warning systems using ESP32-CAM have emerged as a pivotal solution in today's landscape, addressing the growing need for remote monitoring and security. By harnessing the power of ESP32-CAM alongside a suite of compatible sensors and actuators, homeowners can exercise vigilance over their properties from afar. With sensors like DHT22, MQ2, and fire and IR sensors seamlessly integrated, the system stands ready to detect a myriad of potential threats, from temperature fluctuations to gas leaks and even unauthorized intrusions. Leveraging IoT for wireless connectivity, this system facilitates realtime communication, empowering homeowners with immediate alerts and notifications, including visual evidence via Telegram in case of security breaches.

Real Time Chat Application using React and Firebase

Abstract: This paper presents the development of a real-time chat application leveraging modern web technologies, including React for front-end development, Tailwind CSS for styling, and Firebase for backend services. The chat application addresses the need for seamless communication among users in various contexts. We discuss the architectural design, implementation details, and performance evaluation of the application. Our findings demonstrate the effectiveness and scalability of the proposed solution, paving the way for future enhancements and applications in real-time communication systems.

EventPro – Application for Events

Abstract: In recent years, the event management landscape has undergone a profound transformation, driven by the emergence of event apps that have played a pivotal role in this evolution. This abstract delves into the concept of event apps, shedding light on their transformative impact and their potential to revolutionize the entire event lifecycle, encompassing planning, execution, and the overall event experience. Event apps are specialized software applications tailored to streamline the comprehensive event management process. Leveraging the widespread adoption of smartphones and the connectivity of the internet, these digital tools provide a seamless, enhanced event experience for attendees, organizers, and stakeholders. A prominent advantage of event apps is their capacity to simplify the event registration and ticketing process. Attendees can swiftly and conveniently register for events, select sessions, and make payments, effectively reducing the administrative workload for event organizers. Furthermore, event apps offer an array of features, including personalized schedules, interactive maps, and real-time notifications, ensuring attendees can effortlessly navigate events and stay informed about the latest updates. Beyond convenience, event apps foster valuable networking interactions among participants. They facilitate connections, meeting scheduling, and the exchange of contact information, opportunities that might have been challenging to achieve in a traditional event setting. They track attendee engagement, preferences, and behaviors, equipping organizers with insights to tailor future events for maximum impact. Additionally, event apps enable real-time communication, simplifying logistics management and responses to unexpected changes or challenges. As technology continues to advance, the potential for event apps to further revolutionize event planning, execution, and overall experiences is virtually limitless.

SENTINEL GUARD: A FATIGUE DETECTION SYSTEM WITH MULTI-CHANNEL ALERT INTEGRATION

The fatigue detection system is a critical application aimed at enhancing safety in various domains by addressing the risks associated with drowsiness related incidents. Leveraging advanced technologies such as machine learning, computer vision, and real-time communication, the system offers a comprehensive solution for monitoring and alerting users to signs of fatigue in real-time. Through the integration of pre-trained models, such as the shape_predictor_68_face_landmarks.dat, the system accurately detects facial landmarks and tracks eye movements, enabling the identification of drowsiness indicators. Upon detection, the system generates alerts via email and WhatsApp, accompanied by audible alarm buzzers to prompt immediate user intervention. The inclusion of live location information in alerts provides additional context, facilitating timely assistance and support. Furthermore, the system's architecture allows for future enhancements, including the integration of multi-sensor data fusion techniques and collaboration with industry stakeholders to promote standardized protocols and widespread adoption. Overall, the fatigue detection system represents a significant step towards mitigating the risks of drowsinessrelated accidents and improving safety across various applications Key Words: Fatigue detection, Machine learning, CNN, Real time alerts, Facial Expression analysis, Open CV

Smart and Resilient Mobility Services Platform for Managing Traffic Disruptive Events

This article aims to develop a smart mobility solution to enhance the travel experience of individuals facing traffic disruptive events. Unlike prior research focusing on isolated solutions for managing these events, this study takes a holistic approach combining real-time monitoring, predictive modeling, route guidance, and effective communication to create efficient traffic disruption management. The study introduces the Smart and Resilient Mobility Services Platform (SRMS), specifically designed to address mobility restrictions as a form of disruptive events in the Palestinian territories, West Bank. SRMS empowers users to make well-informed decisions by providing services such as real-time mapping of mobility restrictions, a prompt notification system, informal route mapping, and alternative path suggestions. Moreover, it aims to enhance engagement among travelers and citizens by adopting spatial crowdsourcing as the primary data source for potential restrictions and embracing the User-Centered Design (UCD) approach to enrich users’ interaction with the developed solution. The methodology involves presenting the architectural layering system of the SRMS platform, and detailing the prototyping and design development considering the UCD approach. Results present the practical implementation of the SRMS tailored to the Palestinian context and adopted UCD.

A Small Power Margin and Bandwidth Expansion Allow Data Transmission during Rainfall despite Large Attenuation: Application to GeoSurf Satellite Constellations at mm–Waves

The traditional approach of considering the probability distribution of rain attenuation leads to provide very large power margin (overdesign) in data channels. We have extended a method which, with a small power margin, bandwidth expansion and variable symbol rate, avoids overdesign and can transfer the same data volume as if the link were in clear–sky conditions. It is characterized only by the link mean efficiency, suitably defined. It is useful only if: (a) data must be up– and downloaded when it is raining; (b) real–time communication is not required. We have applied it to the links of GeoSurf satellite constellations (in which, at any latitude of ground stations, propagation paths are at the local zenith) by simulating rain attenuation time series at 80 GHz (mm–wave)–the new frontier of satellite frequencies–with the Synthetic Storm Technique, from rain–rate time series recorded on–site, at sites located in different climatic regions. The power margin to be implemented at 80 GHz ranges from 2.0 dB to 7.4 dB–well within the current technology–regardless the instantaneous rain attenuation. The clear–sky bandwidth is expanded 1.75 to 2.80 times, a factor not large per se, but it may challenge current technology if the clear–sky bandwidth is already large.

Adaptive federated reinforcement learning for critical realtime communications in UAV assisted vehicular networks

This paper sheds the light on road active safety measurements implemented in unmanned aerial vehicles assisted vehicular networks. Despite the great potential of deploying high computing drones, the drone battery life is the major concern, on one hand. On the other hand, road active safety is a critical real-time process that should be tackled in a tight time window in vehicular networks. To meet the mentioned concerns, we adopt federated machine learning on the local vehicles, sending local updates to drone servers. Moreover, a dynamic frequency adaptation framework is proposed to achieve the optimal trade-off between the road active safety performance and drone’s energy consumption. The thresholds for the local update frequency are calibrated according to road safety measurements (i.e., collision rate, risky and impolite driving time on the road) and drone energy consumption. Additionally, an accurate mathematical modeling based on M/G/1 multi-class was conducted in order to access the queuing time at the drone.

A Fusion Adaptive Cubature Kalman Filter Approach for False Data Injection Attack Detection of DC Microgrids

With the widespread application of information technology in microgrids, microgrids are evolving into a class of power cyber–physical systems (CPSs) that are deeply integrated with physical and information systems. Due to the high dependence of microgrids’ distributed cooperative control on real-time communication and system state information, they are increasingly susceptible to false data injection attacks (FDIAs). To deal with this issue, in this paper, a novel false data injection attack detection method for direct-current microgrids (DC MGs) was proposed, based on fusion adaptive cubature Kalman filter (FACKF) approach. Firstly, a DC MG model with false data injection attack is established, and the system under attack is analyzed. Subsequently, an FACKF approach is proposed to detect attacks, capable of accurately identifying the attacks on the DC MG and determining the measurement units injected with false data. Finally, simulation validations were conducted under various DC MG model conditions. The extensive simulation results demonstrate that the proposed method surpasses traditional CKF detection methods in accuracy and effectiveness across different conditions.

VEHICLE ACCIDENT DETECTION AND RESCUE SYSTEM

The "Vehicle Accident Detection And Rescue System" project is a cutting-edge endeavour focused on revolutionizing road safety standards. It leverages a combination of sophisticated components, including Arduino Nano microcontrollers, nRF24L01 transceivers, GPS sensors, and SIM800 modules, to create a robust communication network among vehicles. This network enables real-time exchange of crucial information such as accidents and road conditions, empowering drivers with timely insights to navigate safely. Moreover, the project integrates an automatic accident detection system that swiftly responds to collisions by triggering emergency calls to predefined numbers like 100 for police and 108 for medical services. Through this seamless integration of technology, the project aims to mitigate accident risks and enhance overall road safety. Furthermore, the project addresses the challenges associated with overtaking manoeuvrers by introducing a feature that allows drivers to request passage through a simple button press. This functionality facilitates smooth communication between vehicles, ensuring safer overtaking experiences for all road users. By amalgamating state-of-the-art technologies with real-time communication capabilities, the project presents a comprehensive solution to optimize traffic management, reduce accident rates, and ultimately enhance road safety standards. KEY WORDS: Arduino Nano, nrf24L01, GSM Module, GPS Module, OLED

A REVIEW PAPER ON FIRE FIGHTING ROBOT

Firefighting robots are becoming increasingly important tools for combatting fires, particularly in hazardous environments. This paper reviews the latest advancements in real-time wireless firefighting robots. We explore the design considerations, functionalities, and sensor technologies employed in these robots. The paper highlights the importance of autonomous navigation, fire source detection and localization, and fire suppression mechanisms for effective firefighting. We discuss various fire extinguisher options beyond traditional water-based systems to address the limitations of water in extinguishing specific fires. Additionally, the paper examines the role of real-time communication for remote control and data transmission, enabling firefighters to make informed decisions and ensure their safety during operations. Finally, the review concludes by emphasizing the potential of real-time wireless firefighting robots to revolutionize fire response strategies and improve firefighter safety. · Key Words: Firefighting robots, localization, fire suppression mechanisms

Decoding Group Emotional Dynamics in a Web-Based Collaborative Environment: A Novel Framework Utilizing Multi-Person Facial Expression Recognition

As a crucial form of non-verbal communication, facial expressions can convey an individual’s emotional state through a combination of facial muscle movements and provide an effective approach to understanding emotional shifts among group members to a certain extent. However, in real-time collaborative environments, the increasing influx of audiovisual information can overwhelm an individual’s limited visual attention, making it challenging to observe and analyze other group members’ facial expressions continually. The failure to promptly recognize and interpret facial expressions can disrupt individual and group-level comprehension and evaluation of emotional dynamics during collaborative interactions, consequently hindering subsequent emotion management and communication. This article delves into the classification of facial expression information and its formation mechanism to thoroughly analyze the relationship between group members’ emotional perceptions and expressions in the collaboration process. Leveraging the YOLO-FaceV2 face detection model, FaceNet face recognition model, and CERN expression recognition model, we present a novel Collaborative Emotion Analysis Framework (CEAF) for multi-person facial expression recognition. By employing Web real-time communication technology, this framework is integrated into an online group meetings system, which can identify the faces and expressions of the participants and provide real-time visual analysis of their expression information. After the conclusion of the meeting, the system can perform an emotional evaluation with pre-defined operators, providing invaluable insights into the emotional dynamics of the group and individual members throughout the collaborative process. Ultimately, validation through an online meeting instance indicates that this system can facilitate groups in interpreting emotional changes among collaborative group members to a considerable extent.