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This paper presents a healthcare information and medical resource management platform utilizing wearable devices, physiological sensors, and an indoor positioning system (IPS). This platform provides medical healthcare information management based on the physiological information collected by wearable devices and Bluetooth data collectors. The Internet of Things (IoT) is constructed for this medical care purpose. The collected data are classified and used to monitor the status of patients in real time with a Secure MQTT mechanism. The measured physiological signals are also used for developing an IPS. When the patient is out of the safety zone, the IPS will send an alert message instantly by pushing the server to remind the caretaker, easing the caretaker's burden and offering extra protection for the patient. The presented system also provides medical resource management with the help of IPS. The medical equipment and devices can be tracked by IPS to tackle some equipment rental problems, such as lost and found. A platform for the medical staff work coordination information exchange and transmission is also developed to expedite the maintenance of medical equipment, providing the shared medical information to healthcare and management staff in a timely and transparent manner. The presented system in this paper will finally reduce the loading of medical staff during the COVID-19 pandemic period.

Unreliable networks often use excess bandwidth for data integration in smart cities. For this purpose, Messaging Queuing Telemetry Transport (MQTT) with a certain quality of service (QoS) is employed. Data integrity and data security are frequently compromised for reducing bandwidth usage while designing integrated applications. Thus, for a reliable and secure integrated Internet of Everything (IoE) service, a range of network parameters are conditioned to achieve the required quality of a deliverable service. In this work, a QoS-0-based MQTT is developed in such a manner that the transparent MQTT protocol uses Transmission Control Protocol (TCP)-based connectivity with various rules for the retransmission of contents if the requests are not entertained for a fixed duration. The work explores the ways to improve the overall content delivery probability. The parameters are examined over a transparent gateway-based TCP network after developing a mathematical model for the proposed retransmission-based mutant QoS-0. The probability model is then verified by an actual physical network where the repeated content delivery is explored at VM-based MQTT, local network-based broker and a remote server. The results show that the repeated transmission of contents from the sender improves the content delivery probability over the unreliable MQTT-based Internet of Things (IoT) for developing smart cities' applications.

MQTT is one of the most popular application-layer protocols used in the scope of the Internet-of-Things (IoT) and Industrial-Internet-of-Things (IIoT), given its suitability for resource-constrained embedded systems. However, MQTT Quality-of-Service policies do not support timeliness requirements, which is common in IIoT. The literature reports several research works that address this limitation, but they are limited in scope (e.g., improvements in the broker's internal operation, control of the publisher's data rate, and path optimizations). Conversely, this paper presents a comprehensive architectural approach, proposing a set of extensions to the MQTT protocol that allow applications to explicitly specify real-time requirements and instantiate corresponding network reservations to enforce the desired temporal behavior. Such reservations are enforced via Software Defined Networking, specifically the OpenFlow protocol, but other protocols that allow bandwidth reservations, e.g., TSN, can also be used. This paper presents the proposed system architecture together with extensive emulation and implementation results that validate the feasibility of the approach, showing that time-sensitive MQTT traffic can be effectively segregated and prioritized to meet application-defined real-time requirements. Using several combinations of network topologies and load levels and comparing to the absence of the proposed real-time mechanisms, both average and worst-case latencies of the time-sensitive traffic decreased to approximately half, while for the normal traffic, they increased by approximately 10%.

With the evolution of technology, developed systems have become more complex and faster. Thirty years ago, there were no protocols or databases dedicated to developing and implementing IoT projects. We currently have protocols such as MQTT, AMQP, CoAP, and databases such as InfluxDB. They are built to support a multitude of data from an IoT system and scale very well with the system. This paper presents the design and implementation of an IoT alert system that uses MQTT and InfluxDB to collect and store data. We design a scalable system to display assertive alerts on a Raspberry Pi. Each user can select a subset of alerts in our system using a web interface. We present a bibliographic study of SoTA, the proposed architecture, the challenges posed by such a system, a set of tests for the performance and feasibility of the solution, and a set of conclusions and ideas for further developments.

A large number of smart devices in Internet of Things (IoT) environments communicate via different messaging protocols. Message Queuing Telemetry Transport (MQTT) is a widely used publish-subscribe-based protocol for the communication of sensor or event data. The publish-subscribe strategy makes it more attractive for intruders and thus increases the number of possible attacks over MQTT. In this paper, we proposed a Deep Neural Network (DNN) for intrusion detection in the MQTT-based protocol and also compared its performance with other traditional machine learning (ML) algorithms, such as a Naive Bayes (NB), Random Forest (RF), k-Nearest Neighbour (kNN), Decision Tree (DT), Long Short-Term Memory (LSTM), and Gated Recurrent Units (GRUs). The performance is proved using two different publicly available datasets, including (1) MQTT-IoT-IDS2020 and (2) a dataset with three different types of attacks, such as Man in the Middle (MitM), Intrusion in the network, and Denial of Services (DoS). The MQTT-IoT-IDS2020 contains three abstract-level features, including Uni-Flow, Bi-Flow, and Packet-Flow. The results for the first dataset and binary classification show that the DNN-based model achieved 99.92%, 99.75%, and 94.94% accuracies for Uni-flow, Bi-flow, and Packet-flow, respectively. However, in the case of multi-label classification, these accuracies reduced to 97.08%, 98.12%, and 90.79%, respectively. On the other hand, the proposed DNN model attains the highest accuracy of 97.13% against LSTM and GRUs for the second dataset.

Covert channel methods are techniques for improving privacy and security in network communications. These methods consist of embedding secret data within normal network channels, making it more difficult for unauthorized parties to detect such data. This paper presents a new approach for creating covert channels using the Message Queuing Telemetry Transport (MQTT) protocol, widely used in the context of the Internet of Things (IoT). The proposed method exploits storage channels by altering the field length of MQTT messages. Our solution leverages well-known one-way mathematical functions to ensure that data remain hidden from third parties observing the MQTT stream. In this way, we ensure that not only the content of the communication is preserved but also that the communication itself takes place. We conducted a security analysis to show that our solution offers the above-mentioned property even against severe threats, such as an adversary being able to observe all the messages exchanged in the network (even in the clear). Finally, we conducted an overhead analysis of our solution both in terms of the time required to perform the required operations and of the bytes to send. Our study shows that our solution adds no significant time overhead, and the additional overhead in terms of transmitted bytes remains within acceptable limits. [ABSTRACT FROM AUTHOR]

In the context of the internet of things, and particularly within distributed measurement systems that are subject to high privacy risks, it is essential to emphasize the need for increasingly effective privacy protections. The idea presented in this work involves managing critical traffic through an architectural proposal aimed at solving the problem of communications between nodes by optimizing both the confidentiality to be guaranteed to the payload and the transmission speed. Specifically, data such as a typical sensor on/off signal could be sent via a standard encrypted channel, while a sensitive aggregate could be transmitted through a dedicated private channel. Additionally, this work emphasizes the critical importance of optimizing message sizes to 5 k-bytes (small payload messages) for transmission over the reserve channel, enhancing both privacy and system responsiveness, a mandatory requirement in distributed measurement systems. By focusing on small, encrypted payloads, the study facilitates secure, timely updates and summaries of network conditions, maintaining the integrity and privacy of communications in even the most challenging and privacy-sensitive environments. This study provides a comprehensive performance analysis of IoT networks using Dark Net technologies and MQTT protocols, with a focus on privacy and anonymity. It highlights the trade-offs between enhanced security and performance, noting increased latency, reduced bandwidth, and network instability when using TOR, particularly with cipher suites like AES256-GCM-SHA384 and DHE-RSA-CHACHA20-POLY1305. The research emphasizes the need for further exploration of alternative protocols like LWM2M in secure IoT environments and calls for optimization to balance privacy with performance in Dark-Net-based IoT deployments. [ABSTRACT FROM AUTHOR]

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The power grid, manufacturing, and industrial automation are just a few Internet of Things (IoT) settings where publish/subscribe (p/s) systems are increasingly prevalent. These systems may handle a wide range of middleware and communication protocols, ensuring compatibility. The most well-liked publish/subscribe protocol is the Message Queue Telemetry Transport Protocol (MQTT), which uses an agent to transfer information between publishers and subscribers on certain subjects. MQTT can be quickly and simply deployed for IoT settings using a popular wireless MAC layer protocol like Long Range Wide Area Network (LoRaWAN), however, this has not been properly validated. MQTT can be readily set up in cloud environments to do research experiments. To provide an MQTT-based publication design that can handle the LoRaWAN proactive steps, the authors design and provide a simulation framework in NS-3 in this study. To do this, the authors make use of the LoRaWAN library from NS-3 and include connecting it with a middleman that links to numerous publications as well as clients. The authors support many topics at the broker while enabling unicast capabilities from the broker to LoRaWAN end devices. In other words, the proposed work activates the unicast capability from the middleman to LoRaWAN peripheral devices while handling multiple topics at the mediator. To illustrate the viability of our IoT architecture and evaluate its performance at scale, the authors performed several scenarios under it. [ABSTRACT FROM AUTHOR]

The applications of IoT have increased manyfold owing to the declining prices of electronic devices and the growing internet. This study discusses at length the various characteristics, applications, merits, demerits, and problems associated with IoT. The current research work showcases the design and development of application coined as MIAWM: MQTT based IoT Application for Weather Monitoring. The application describes how the MQTT protocol can easily be used to perform efficient routing in IoT. The Application describes how to create a simulation for the MQTT Publisher Subscriber model which provides desired weather data to a remote subscriber anywhere in the world. The dataset used contains information about the temperature, precipitation, and wind speed in Berlin and Germany. This paper puts the various quality of service to experiment by comparing the time taken to service the request. [ABSTRACT FROM AUTHOR]

The growth of Internet of Things (IoT) devices has created opportunities in multiple sectors, but has also created the threat of growing attacks. Malicious actors are taking advantages of the lightweight nature of IoT devices and targeting them to perform attacks. This paper presents a novel approach to detect malicious traffic at an early stage to block attacks at the entry point of network so devices could be protected from getting infected. An optimized Machine Learning(ML) based algorithm is proposed specifically designed for light weighted IoT devices. The IoT- 23 dataset is used in this study to create a model and test the performance. The proposed model detects diverse categories of IoT malwares, creating security threats and challenges to IoT systems. MQTT (Message Queuing Telemetry Transport) is utilized to simulate behavior of IoT devices. Attack and normal traffic is passed to the IoT network to record latency and throughput in both scenarios. Performance of five different classifiers is compared with the proposed algorithm and had outstanding results with an accuracy 99.98%. The detection model takes around 52.89 seconds and processes 3965.27 samples per second. Utilization of CPU during the entire process is observed around 3.5%. Future research directions and suggestions have also been given to enhance the security of IoT environment. [ABSTRACT FROM AUTHOR]

The Message Queuing Telemetry Transport (MQTT) protocol, widely used in various industries for Machine-to-Machine (M2M) communication, plays a central role in the IoT architecture. However, despite its widespread adoption, an analysis conducted on the shodan search engine revealed up to 540531 vulnerabilities worldwide as of April 2024, underscoring the security challenges facing this protocol. How can an innovative cyber range system be designed to assess and improve the security of MQTT protocols, focusing on in-depth vulnerability analysis, authentication strategy development, and targeted countermeasures against specific attacks? The study includes an analysis of relevant articles, followed by classification into five different categories. Furthermore, the presentation of a cyber range that exposes various attacks, such as replay attacks, Man-In-The-Middle (MITM), Denial of Service (DoS)/Distributed DoS(DDoS), and cam-hackers, enhances the understanding of MQTT protocol vulnerabilities, emphasizes the critical importance of strengthening security, and serves as a reference for new researchers in the field. [ABSTRACT FROM AUTHOR]

To overcome the issues of the existing properties and the non-configurable supervisory control and data acquisition (SCADA) architecture, this paper proposes an IoT-centered open-source SCADA system for monitoring photovoltaic (PV) systems. The system consists of three voltage sensors and three current sensors for data accumulation from the PV panel, the battery, and the load. As a part of the system design, a relay is used that controls the load remotely. An ESP32-E microcontroller transmits the collected data to a Banana Pi M4 Berry (BPI-M4 Berry) through the Message Queuing Telemetry Transport (MQTT) protocol over a privately established communication channel using Wi-Fi. The ESP32-E is configured as the MQTT publisher and the BPI-M4 Berry serves as the MQTT broker. Locally installed on the BPI-M4 Berry, the Node-RED platform creates highly customizable dashboards as human–machine interfaces (HMIs) to achieve real-time monitoring of the PV system. The proposed system was successfully tested to collect the PV system voltage/current/power data and to control the load in a supervisory way under a laboratory setup. The complete SCADA architecture details and test results for the PV system data during the total eclipse on 8 April 2024 and another day are presented in this paper. [ABSTRACT FROM AUTHOR]

The widespread adoption of Internet of Things (IoT) devices in home, industrial, and business environments has made available the deployment of innovative distributed measurement systems (DMS). This paper takes into account constrained hardware and a security-oriented virtual local area network (VLAN) approach that utilizes local message queuing telemetry transport (MQTT) brokers, transport layer security (TLS) tunnels for local sensor data, and secure socket layer (SSL) tunnels to transmit TLS-encrypted data to a cloud-based central broker. On the other hand, the recent literature has shown a correlated exponential increase in cyber attacks, mainly devoted to destroying critical infrastructure and creating hazards or retrieving sensitive data about individuals, industrial or business companies, and many other entities. Much progress has been made to develop security protocols and guarantee quality of service (QoS), but they are prone to reducing the network throughput. From a measurement science perspective, lower throughput can lead to a reduced frequency with which the phenomena can be observed, generating, again, misevaluation. This paper does not give a new approach to protect measurement data but tests the network performance of the typically used ones that can run on constrained hardware. This is a more general scenario typical for IoT-based DMS. The proposal takes into account a security-oriented VLAN approach for hardware-constrained solutions. Since it is a worst-case scenario, this permits the generalization of the achieved results. In particular, in the paper, all OpenSSL cipher suites are considered for compatibility with the Mosquitto server. The most used key metrics are evaluated for each cipher suite and QoS level, such as the total ratio, total runtime, average runtime, message time, average bandwidth, and total bandwidth. Numerical and experimental results confirm the proposal's effectiveness in foreseeing the minimum network throughput concerning the selected QoS and security. Operating systems yield diverse performance metric values based on various configurations. The primary objective is identifying algorithms to ensure suitable data transmission and encryption ratios. Another aim is to explore algorithms that ensure wider compatibility with existing infrastructures supporting MQTT technology, facilitating secure connections for geographically dispersed DMS IoT networks, particularly in challenging environments like suburban or rural areas. Additionally, leveraging open firmware on constrained devices compatible with various MQTT protocols enables the customization of the software components, a crucial necessity for DMS. [ABSTRACT FROM AUTHOR]

The security and integrity of medical data, in particular, have become significant concerns due to the substantial expansion in the healthcare environment due to the internet of things (IoT). To guarantee data security during transmission, this research suggests a chaotic healthcare monitoring system. This system employs a new 5- dimension (5D) chaotic system in conjunction with the secure hash algorithm version three (SHA3-256), salsa 20, and deoxyribonucleic acid (DNA). Lyapunov's proposed 5D chaos system was tested and passed for several initial periods, yielding a super chaos system (3 positive Lyapunov). Salsa 20 and randomly generated chaotic keys were utilized for encryption and decryption operations. The method we created will assess a patient's body temperature, heart rate, and oxygen saturation levels in the blood and communicate the data to a healthcare center through the Message Queuing Telemetry Transport (MQTT) protocol. The suggested system ensures that patient data is transmitted via the internet or an intranet in a secure, reliable, and readily accessible manner. In several studies involving security analysis, The encryption time is 1.872, the throughput (in bits per second (bps)) is 273.2642, and the memory usage (in megabytes) is 10.6211. The performance analysis confirmed the proposed cryptosystem's capacity to withstand multiple attacks due to its low computational and communication costs and broad key space. [ABSTRACT FROM AUTHOR]

In this paper, we conducted a state-of-the-art survey on the current state of IoT platforms suitable for the development of smart city (SC) applications. Both commercial and open-source IoT platforms are presented and compared, addressing various significant aspects and characteristics of SC applications, such as connectivity, communication protocols, dashboards/analytics availability, security, etc. The characteristics of all the investigated platforms were aggregated so that useful outcomes regarding the technological trends of the IoT platforms could be derived. Furthermore, an attempt was made to identify any discrepancies between the needs of smart cities and the capabilities provided by the relevant platforms. Moreover, IoT platforms referring to the domains of industry, agriculture, and asset tracking were also included, alongside platforms that purely target smart cities, as parts of them are also applicable to smart city applications. The results of the comparison proved that there is a lack of open-source IoT platforms targeted at smart cities, which impedes the development and testing of connected smart city applications for researchers. [ABSTRACT FROM AUTHOR]

With the rapid development of the Internet of Things (IoT) in recent years, many IoT devices use communication systems to transmit data. Data packets are inevitably at risk of tampering during data transmission, which can lead to information errors and damage during communication. Since IoT terminals are often operated under human supervision, it is essential to improve and ensure the transmission of information, avoid data tampering, and ensure the accuracy of packet transmission. This research successfully improves the message transmission method of IoT communication and the communication model by combining it with blockchain architecture. Combining communication protocols with blockchain serial connections eliminates the need to control operating and managing processes. By replacing message transmission with coverage, the reliability of data transmission in the IoT communication system is improved, and the flexibility of the data transmission process is enhanced. Through practical verification through experimentation, the study successfully improved the incapability of effectively constructing a cross-coded message transmission mode in the Message Queuing Telemetry Transport (MQTT) communication protocol, removed a single layer of encryption rule, and created an encryption mode capable of providing complex arrangement organization. [ABSTRACT FROM AUTHOR]

The escalating advancement in Software-Defined Vehicles (SDVs) necessitates a formidable strategy for firmware updates, where traditional methods often fall short of guaranteeing absolute integrity. Although decentralization has been explored in studies for firmware integrity verification using blockchain technology, it lacks comprehensive validation in the context of automotive over-the-air (OTA) updates. By recognizing the limitations of current practices and the partial validation of decentralized approaches, such as blockchain, in the automotive sector, our study introduces a novel mechanism for firmware over-the-air (FOTA) updates. This mechanism is grounded in the widely adopted message queuing telemetry transport (MQTT) protocol, integral to the Internet of Things (IoT) domain, and leverages Merkle tree-based blockchain verification to fortify the fidelity and efficiency of firmware updates. Our proposed solution not only prioritizes the stability crucial to automotive OTA updates but also ensures that performance is not compromised. This dual focus on reliability and efficiency represents a significant stride forward in the development of secure, scalable SDV firmware update protocols. [ABSTRACT FROM AUTHOR]

Urban farming has been growing in popularity to help secure food needs in urban areas. Hydroponic is one of the methods to grow crops without soil media being an option for urban farming. However, hydroponic farming has its challenges as farmers must carefully monitor the environmental conditions of the plants regularly and adjust the nutrient solution and water circulation based on the environmental conditions. This paper describes designing and implementing an IoT-enabled hydroponic farming system to monitor the environmental condition of plants and control the nutrient supply plants. Our system is built from sensors, actuators, a micro-controller unit (Arduino), and a single-board computer (Raspberry pi) attached to the hydroponic system. The system can monitor the environmental condition of hydroponics through sensors such as temperature, humidity, pH sensors, and Total Dissolve Solid (TDS) sensors and control water pumps to circulate the nutrients to the plant. The Raspberry pi acts as a Message Queuing Telemetry Transport (MQTT) broker for distributing the data from sensors to subscribers. It also controls the nutrient pump to adjust nutrient solution. We use Node-RED installed in the Raspberry pi to build and connect the system to hardware devices. Users can monitor the environmental condition of plants in hydroponics through a web browser on their smartphone and laptop. This IoT-based indoor hydroponic system can automate the delivery of nutrients and water to plants, ensuring they receive the optimal amount at the right time. [ABSTRACT FROM AUTHOR]

The fast evolution of Industry 4.0 and smart manufacturing has led to an increased reliance on MQTT (Message Queuing Telemetry Transport) as a lightweight messaging protocol for efficient machine-to-machine communication. Despite MQTT being well-suited as a standard protocol for the Industrial Internet of Things and the increasing provision of MQTT interfaces by manufacturers for their production machines, the presence of poorly documented, non-machine-readable APIs poses challenges. Consequently, integrating these devices into an existing production environment requires significant effort and is prone to errors. In this paper, we explore diverse methods for extracting valuable information from running MQTT clients, enabling the reconstruction of their communication interfaces with the associated endpoints. This information can then be transformed into a standardized machine-readable format. The AsyncAPI Initiative has defined such an industry standard for defining asynchronous APIs, which includes MQTT. These AsyncAPI Specifications can be used to make a subsequent implementation of programs that interact with these interfaces more fast and reliable. The presented approaches focus on extracting interface information by analyzing network traffic and MQTT messages. We concentrate on observing the behavior of MQTT clients from an external perspective, deliberately disregarding the internal workings and program code of the clients themselves. Furthermore, we discuss an approach to map the data from the intercepted MQTT communication to a AsyncAPI Specification. Through our research, we aim to provide insights into the various techniques that can be employed to reverse engineer MQTT client interfaces effectively. By leveraging these approaches, it is possible to gain valuable knowledge about MQTT client communication interfaces, thus simplifying the subsequent implementation of programs that interact with these interfaces. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) is spreading rapidly around the world, and Message Queue Telemetry Transport (MQTT) is one of the main protocols used to explore device-to-device (D2D) communication. The industry typically requires communication systems that can transmit data continuously while optimizing both bandwidth and transmission time. Due to the vast amount of data that can be lost, companies often find that even short periods of network downtime lead to significant costs. In this paper, we propose a retransmission mechanism to allow sensor nodes to relay missing data via MQTT to a local server when it reconnects after an unexpected disconnection. To assess its performance, several tests in a digital healthcare use case scenario have been designed. Since the procedure involves transferring a considerable amount of data, our main goal is to determine the maximum payload of each message to restore the missing information, while minimizing the retransmission time without information loss. [ABSTRACT FROM AUTHOR]

Deployment of IoT devices into an existing control system has increasingly become a new norm in recent years. Traditional approach of installing a new device into the system involves creating a separate network or infrastructure to ensure that the newly added devices do not affect the current system. However, this may not be the optimal solution for IoT devices, as they are designed to integrate and communicate with the existing systems. Therefore, it is important to understand how to properly deploy IoT devices and address the concerns of engineers. This research shares valuable experiences in deploying and integrating IoT devices into a campus Building Management System It covers considerations and requirements for the devices, as well as the deployment and integration challenges encountered during the process. These valuable experiences can serve as a useful reference for the industry when they need to install IoT devices in their infrastructure. [ABSTRACT FROM AUTHOR]

Greenhouses have long been important in the advancement of agricultural operations because they provide regulated settings for optimal plant growth. With the introduction of real-time monitoring and automation capabilities, the Internet of Things (IoT) integration into greenhouse systems represents a revolutionary change. This abstract delves into the wider field of greenhouse technology, highlighting the role that IoT plays in improving agricultural in controlled environments. Conventional greenhouses provide plants with a protected environment, but they might not be as accurate or flexible. Intelligent control of environmental conditions is made possible by the introduction of IoT-enabled greenhouses, which utilize data exchange protocols, actuators, and sensors that are networked. The project aims to elevate traditional greenhouse models by integrating Node-RED and MQTT technologies. Transitioning from a Blynk-based prototype showcases the system's versatility. Other key components, including NodeMCU, sensors for real-time data, and LED lighting, collaborate to redefine controlled environment agriculture. The Raspberry Pi serves as a central hub, facilitating seamless communication through Node-RED and MQTT. This advanced greenhouse system harmonizes cutting-edge technologies, showcasing a commitment to sophistication and adaptability in agricultural practices.

The rapid growth of the Internet of Things (IoT) has raised security concerns, including MQTT protocol-based applications that lack built-in security features and rely on resource-intensive Transport Layer Security (TLS) protocols. This paper presents an approach that utilizes blockchain technology to enhance the security of MQTT communication while maintaining efficiency. This approach involves using blockchain sharding, which enables higher scalability, improved performance, and reduced computational overhead compared to traditional blockchain approaches, making it well-suited for resource-constrained IoT environments. This approach leverages Ethereum blockchain's smart contract mechanism to ensure trust, accountability, and user privacy. Specifically, we introduce a shard-based consensus mechanism that enables improved security while minimizing computational overhead. We also provide a user-controlled and secured algorithm using Proof-of-Access implementation to decentralize user access control to data stored in the blockchain network. The proposed approach is analyzed for usability, including metrics such as bandwidth consumption, CPU usage, memory usage, delay, access time, storage time, and jitter, which are essential for IoT application requirements. The analysis demonstrated that the approach reduces resource consumption, and the proposed system outperforms TLS and existing blockchain approaches in these metrics, regardless of the choice of the MQTT broker. Additionally, thoroughly addressing future research directions, including issues and challenges, ensures careful consideration of potential advancements in this domain.

In modern large hotels, due to a large number of rooms and complex layouts, it is difficult for customers to find rooms, which increases a lot of workloads for hotel attendants to guide. In this paper, a hotel intelligent guidance system based on face recognition is designed. After entering the customer's facial photos, the room guidance and customer management are carried out through face recognition. With this, hotels can move toward card-free management, green environmental protection, and save on resources. With these improvements, hotel management will be card-free and green. Each monitoring device of the system adopts dual STM32 core architecture, in which STM32H7 is responsible for face recognition, while STM32L4 is the main control chip, which is responsible for data exchange, guest room guidance and other work. The monitoring master not only guides, but also uploads customer check-in information to the cloud platform to facilitate the management of the hotel. The system adopts contactless information collection and guidance, which improves the intelligence and humanization of the hotel, and has a good application prospect. [ABSTRACT FROM AUTHOR]

An IoT-based wireless centralized monitoring system has been proposed which is an effective way to monitor and control building systems. The system will serve the purpose of replacing an old and expensive PLC-based and wire-based management system. The system here uses several nodes of networks which are connected through wireless mesh and sending data to the centralized edge computing device (raspberry pi) through MQTT protocol. Then, the edge will update the data on the cloud using Firebase to generate a library and update the data on the cloud on a real-time basis and through the cloud, which will then allow us to monitor and control the system through the website which can be used easily and remotely on any browsing device. [ABSTRACT FROM AUTHOR]

This research project takes a holistic strategy to improve QoS and security in SDN-based IoT networks. We offer an intricate solution with a federated autoencoderbased tool to precisely identify malicious network traffic in response to the expanding IoT ecosystem and its security issues. We use a QoS dashboard coupled with OpenDaylight to monitor latency, throughput, packet loss, and jitter, dynamic resource allocation based on device priorities, and better MQTT AES encryption. These elements constitute a framework for SDN-based IoT networks' changing needs. Global autoencoder models with client models on IoT devices provide real-time anomaly detection in our system. We offer a packet manipulator to generate tailored network traffic samples for robust model training. The OpenDaylight-integrated QoS dashboard gives administrators real-time network performance data. A priority-based resource allocation system allocates resources by device significance to preserve QoS during peak demand. AES encryption for MQTT, a popular IoT standard, is also improved. It protects critical IoT data from security risks. Our Mininetbased Ubuntu simulations show that our technique maintains QoS, detects network anomalies, and strengthens IoT network security. These findings show that our methodology may improve SDN-based IoT deployment reliability and security, creating a more resilient and secure ecosystem. [ABSTRACT FROM AUTHOR]

In order to study the standard security access authentication mechanism of intelligent sensing terminals of massive power Internet of Things, In order to study the standard secure access authentication mechanism of intelligent sensing terminal of massive power Internet of Things, a new privacy protection method widely used in block chain is proposed to prove identity. The traditional power IoT cloud-side interaction security access MQTT protocol still has a lot of room for adaptation and optimization. First, the proposed non-interactive zero-knowledge proof identity authentication method reduces the time of traditional standard secure access authentication process; Second, it reduced the computing resources consumed in a large number of intelligent sensors access authentication. The comparison results show that, the access authentication time of this method is 30% ∼ 50% less than that of the traditional secure access authentication process. The computing resources consumed during authentication are reduced by 20% to 30% compared with traditional security and secrecy mechanisms. [ABSTRACT FROM AUTHOR]

Predictive maintenance is a vital aspect of the industrial sector, and the use of Industrial Internet of Things (IIoT) sensor nodes is becoming increasingly popular for detecting motor faults and monitoring motor conditions. An integrated approach for acquiring, processing, and wirelessly transmitting a large amount of data in predictive maintenance applications remains a significant challenge. This study presents an IIoT-based sensor node for industrial motors. The sensor node is designed to acquire vibration data on the radial and axial axes of the motor and utilizes a hybrid approach for efficient data processing via edge and cloud platforms. The initial step of signal processing is performed on the node at the edge, reducing the burden on a centralized cloud for processing data from multiple sensors. The proposed architecture utilizes the lightweight Message Queue Telemetry Transport (MQTT) communication protocol for seamless data transmission from the node to the local and main brokers. The broker's bridging allows for data backup in case of connection loss. The proposed sensor node is rigorously tested on a motor testbed in a laboratory setup and an industrial setting in a rice industry for validation, ensuring its performance and accuracy in real-world industrial environments. The data analysis and results from both testbed and industrial motors were discussed using vibration analysis for identifying faults. The proposed sensor node is a significant step towards improving the efficiency and reliability of industrial motors through realtime monitoring and early fault detection, ultimately leading to minimized unscheduled downtime and cost savings. [ABSTRACT FROM AUTHOR]

Nowadays, the cybersecurity of Internet of Thing (IoT) environments is a big challenge. The analysis of network traffic and the use of automated estimators built up with machine learning techniques have been useful in detecting intrusions in traditional networks. Since the IoT networks require new and particular protocols to control the communications between the different devices involved in the networks, the knowledge acquired in the study of general networks may be unuseful some times. The goal of this paper is twofold. On the one hand, we aim to obtain a consistent dataset of the network traffic of an IoT system based on the Message Queue Telemetry Transport protocol (MQTT) and undergoing certain type of attacks. On the other hand, we want to characterize each of these attacks in terms of the minimum possible number of significant variables allowed by this protocol. Obtaining the data set has been achieved by studying the MQTT protocol in depth, while its characterization has been addressed through a hybrid (filter/wrapper) feature selection algorithm based on the idea behind the minimum-redundancy maximum-relevance (mRMR) algorithm. The dataset, together with the feature selection algorithm, carries out a characterization of the different attacks which is optimal in terms of the accuracy of the machine learning models trained on it as well as in terms of the capability of explaining their underlying nature. This confirms the consistency of the dataset. [ABSTRACT FROM AUTHOR]

The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient communication between the sensors, gateway devices, and the cloud server. The system was tested on an operational motors dataset, five machine learning algorithms, namely k-nearest neighbor (KNN), supported vector machine (SVM), random forest (RF), linear regression (LR), and naive bayes (NB), are used to analyze and process the collected data to predict motor failures and offer maintenance recommendations. Results demonstrate the random forest model achieves the highest accuracy in failure prediction. The solution minimizes downtime and costs through optimized maintenance schedules and decisions. It represents an Industry 4.0 approach to sustainable smart manufacturing. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) is the interconnection of devices with the internet to deliver its tasks. Nowadays, security is the main concern relating to these devices. Low in power storage, low in processing capabilities and low in data storage make it hard to provide a strong set of security protocols to protect the vulnerable devices "things". Having internet as its backbone, allows the devices to communicate seamlessly. However, without any form of protection, it would open the door for hackers or middleman to hijack the connection, steal data and sabotage the information. In this paper, Secure Socket Layer and Transport Layer Security (SSL/TLS) protocol is implemented on top of Message Queuing Telemetry Transport (MQTT) IoT application protocol and the performance of the network is evaluated and analyzed in a typical IoT testbed comprising Raspberry Pi4 and ESP32 nodes. This work focuses on energy consumption, generated overhead, system complexity and required data storage resources. Experimental results of stress testing the system indicates that SSL/TLS encryption, operating with MQTT Quality of Service (QoS) level 2, while increasing the traffic rate 3.5 orders of magnitude yields more than two thousand times the amount of overhead generated and results in 73.25 J of consumed energy. Whereas operating without the SSL/TLS encryption under the same stress testing conditions yields only 140 times the amount of overhead generated and results in a mere 18.76 J of consumed energy. This difference of 4 folds on consumed energy indicates that the SSL/TLS -enabled node battery can only last a quarter of the lifespan of the TLS-free node and concluding the SSL/TLS encryption is not a viable solution for battery-operated IoT nodes. [ABSTRACT FROM AUTHOR]

To meet the needs of environmental monitoring and regulation in rabbit houses, a real-time environmental monitoring system for rabbit houses was proposed based on narrow band Internet of Things (NB-IoT). The system overcomes the limitations of traditional wired networks, reduces network costs, circuit components, and expenses is low. An Arduino development board and the Quectel BC260Y-NB-IoT network module were used, along with the message queuing telemetry transport (MQTT) protocol for remote telemetry transmission, which enables network connectivity and communication with an IoT cloud platform. Multiple sensors, including SGP30, MQ137, and 5516 photoresistors, were integrated into the system to achieve real-time monitoring of various environmental parameters within the rabbit house, such as sound decibels, light intensity, humidity, temperature, and gas concentrations. The collected data was stored for further analysis and could be used to inform environmental regulation and monitoring in rabbit houses, both locally and in the cloud. Signal alerts based on circuit principles were triggered when thresholds were exceeded, creating an optimal living environment for the rabbits. The advantages of NB-IoT networks and other networks, such as Wi-Fi and LoRa were compared. The technology and process of building a system based on the three-layer architecture of the Internet of Things was introduced. The prices of circuit components were analyzed, and the total cost of the entire system was less than 400 RMB. The system underwent network and energy consumption tests, and the transmission stability, reliability, and energy consumption were reasonable and consistent across different time periods, locations, and network connection methods. An average of 0.57 transactions per second (TPS) was processed by the NB-IoT network using the MQTT communication protocol, and 34.2 messages per minute were sent and received with a fluctuation of 1 message. The monitored device was found to have an average voltage of approximately 12.5 V, a current of approximately 0.42 A, and an average power of 5.3 W after continuous monitoring using an electricity meter. No additional power consumption was observed during communication. The performance of various sensors was tested through a 24-hour indoor test, during which temperature and lighting conditions showed different variations corresponding to day and night cycles. The readings were stably and accurately captured by the environmental sensors, demonstrating their suitability for long-term monitoring purposes. This system is can provide equipment cost and network selection reference values for remote or large-scale livestock monitoring devices.

Nowadays, the world of the Internet of Things (IoT) enables machines to communicate, collect data, and even make decisions which improve significantly daily human life. However, the proliferation of IoT devices coupled with their inherent vulnerabilities makes them highly exposed to cyber-attacks such as network disruptions or Denial of Service (DoS) attacks. Traditional detection methods based on a single machine learning (ML) technique may not be fully efficient due to the sophistication level and the variety of attacks. In this paper, we propose an intrusion detection model based on ensemble learning (EL) trained using a recent public dataset containing various MQTT attacks. EL is a powerful machine learning (ML) technique that consists of training several ML models independently on random subsets of the training data and then averages the predictions to produce the final result. Basically, we propose the use of three known ensemble learning methods, namely bagging, boosting, and stacking. EL principles allow increasing prediction performances by integrating the capabilities of numerous distinct models. In order to train and test the proposed model, we also propose generating a binary balanced MQTT dataset rather than using imbalanced one as usually used in previous work. To the best of our knowledge, the work in this paper is the first that applies ensemble learning method on this MQTT dataset. The experiment results have shown that our EL-based network IDS increases both the detection accuracy and F1-score up to 95% where Matthews's correlation coefficient (MCC) exceeds 90%. [ABSTRACT FROM AUTHOR]

As Internet of Things (IoT) thrives over the whole world, more and more IoT devices and IoT-based protocols have been designed and proposed in order to meet people’s needs. Among those protocols, message queueing telemetry transport (MQTT) is one of the most emerging and promising protocols, which provides many-to-many message transmissions based on the “publish/subscribe” mechanism. It has been widely used in industries such as the energy industry, chemical engineering, self-driving, and so on. While transporting important messages, MQTT specification recommends the use of TLS protocol. However, the computation cost of TLS is too heavy. Since topics in a broker are stored with a hierarchical structure, in this manuscript, we propose a novel data protection protocol for MQTT from hierarchical ID-based encryption. Our protocol adopts the intrinsic hierarchical structures of MQTT, and achieves constant-size keys, i.e., independent of the depth in hierarchical structures. Besides, the formal security model for the proposed protocol have been defined in the manuscript. The proposed protocol have been formally proven chosen-plaintext secure under the -wBDHI assumption. [ABSTRACT FROM AUTHOR]