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In the age of high-tech automation and wireless technology, it is possible to make various devices come together in a given environment, enhancing comfort, energy savings, security, and affordability. We can observe environmental indicators remotely and manage relevant equipment with embedded systems' tiny, low-energy consumption. These devices' power consumption and network bandwidth utilization are critical. Thus, a low-power device must transfer data using minimal redundant protocol. Since Wi-Fi is so widely available, linking all devices within the space through one standard gateway makes sense. This study gives an overview of Message Queuing Telemetry Transport (MQTT), an ideal lightweight protocol for such applications because of its low power and bandwidth requirements. The proposed prototype uses MQTT on the ESP8266, a Wi-Fi-based expansion board. In the case of ESP8266, sensors and actuators are connected directly using Cayenne-based MQTT brokers to provide remote control and monitoring. It allows for efficient and effective communication within the network, ensuring stable data transmission and device management while minimizing power consumption and bandwidth usage. The project has shown how possible it is to use MQTT in the ESP8266 to support smart environments, leading to better IoT-integrated solutions. [ABSTRACT FROM AUTHOR]

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]

Networks for the Internet of Things typically use a gateway to provide connectivity between a low bit rate, low capability sensor network and the broader Internet. The gateway can be subject to very high traffic loads, many concurrent processes and needs to be highly reliable. Functional programming languages such as Erlang and Elixir have proven to be an effective programming paradigm for such scenarios, notably in large-scale telecommunications switches. In this paper, we report on our experience of developing a gateway between a LoRa network and an MQTT broker using the functional programming language Elixir and the more conventional language C++. To obtain an understanding of this approach to development, we first developed an initial prototype on a single-board computer using Elixir. We then developed the same system in C++ and ran experiments to compare the two systems' performance. In order to understand the performance of such systems on low-end IoT devices, we then developed the same system on a low-cost ESP32 micro-controller in both C++ and Elixir. We were able to run the Elixir-based system on an ESP32 micro-controller but found that its performance was significantly poorer than the same system written in C++. We conclude that functional programming has great potential for the development of IoT systems, but work needs to be carried out to improve the supporting libraries and underlying virtual machines. We also note that learning to program in a functional programming language has quite a steep learning curve. [ABSTRACT FROM AUTHOR]

In the evolving digital landscape, interconnected IoT networks are expanding fast. However, essential security measures are often lacking, which makes it vulnerable to cyber threats. Intrusion Detection Systems (IDSs) are crucial in combating these threats, but IDSs in the IoT domain face significant challenges; one of them is the existence of imbalanced data, where attack activities are underrepresented compared to normal activities. This becomes a problem when handling Machine Learning (ML) tasks to improve the system’s intrusion detection ability. This paper presents a novel solution by leveraging Generative Adversarial Networks (GANs) to create balanced datasets. Unlike traditional methods, our approach generates high-quality synthetic samples that maintain the intricate characteristics of the data, making it possible to improve detection accuracy. Additionally, we introduce three specialized IDSs designed to detect attacks on the lightweight Message Queuing Telemetry Transport (MQTT) protocol, utilizing hybrid Deep Learning (DL) algorithms (CNN-RNN, CNN-LSTM, and CNN-GRU). Experimental results, using a combination of both the original MQTT dataset and a newly generated dataset through GANs, demonstrate the better performance of the generated datasets in multi-class classification. This performance highlights the effectiveness of our GAN-based approach in improving detection accuracy at the same time that it reduces false positives. The ultimate objective is to develop an autonomous system tailored to safeguard IoT environments, providing a robust and adaptable solution to emerging cyber threats. [ABSTRACT FROM AUTHOR]

IoT application uses MQTT, an application layer protocol that facilitates machine-to-machine communication using a central entity called broker. The vulnerability lies in the broker being susceptible to intrusion attempts, where a potential attacker might engage in a Distributed Denial of Service attack. Such an attack involves repetitively transmitting large number of malicious messages or counterfeit connect requests. To send large messages, the attackers must breach the authentication process of MQTT. MQTT employs two authentication approaches to safeguard its system: certificate-based and credential-based authentication. Credential-based authentication is popular as it is easy to implement. However, in MQTT, credential-based authentication is vulnerable to various attacks as credentials are transmitted in plain-text form. In literature, authors have explored different cryptography-based solutions to address these challenges. However, implementing these solutions in IoT systems is impractical due to the substantial computational requirements at the broker and the end devices. The primary objective of this work centres around formulating a PUF-based authentication policy and designing an IDS to track the behaviour of incoming traffic. In the proposed authentication scheme, the PUF mechanisms generate credentials to establish authenticity, thus protecting the network from password-based vulnerabilities like dictionary-based attacks. The second security module of this research implements a Machine Learning based IDS system to track and block fake connect requests in real-time. The proposed IDS system comprises Decision Tree and Neural Network algorithms that operate in parallel. In order to maintain the lightweight nature of the ML model, the system incorporates a feature selection technique. The result section shows that the proposed system effectively and efficiently recognizes fake connect requests in real-time and consumes minimal energy. Additionally, the proposed scheme requires less time than existing schemes in the literature. [ABSTRACT FROM AUTHOR]

Over the last decade, health information systems (HIS) have undergone significant changes, particularly in embracing flexible frameworks for ongoing development. This evolution underscores the necessity for information technology (IT) infrastructures that rapidly align with clinical processes. The paper investigates the transition of hospital information systems to comprehensive strategies, examining the benefits and challenges involved. It also examines the increasing demands on health data management systems (HDMS) for patient care and biomedical research. The focus is on how the integration of the Internet of Things (IoT) and open-source enterprise resource planning (ERP) systems, such as Odoo, impacts health information management. The study evaluates the effectiveness and implications of combining these technologies. It provides examples of these integrated systems in action, particularly in resource-limited settings, and evaluates their potential to improve care. The document provides a comprehensive review of the current status and evolution of HIS and HDMS, highlighting the importance of integrating IoT and other cutting-edge technologies in healthcare. This is a crucial aspect for developing countries, where these advancements can significantly improve healthcare outcomes. [ABSTRACT FROM AUTHOR]

Copyright of Techno.com is the property of Universitas Dian Nuswantoro, Fakultas Ilmu Komputer and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

With the gradual increase in the proportion of new energy sources in the power grid, there is an urgent need for more flexible resources to participate in short-term regulation. The impact of communication network channel quality will continue to magnify, and factors such as communication latency may directly affect the efficiency and effectiveness of resource regulation. In this context of a large number of flexible demand-side resources accessing the grid, this article proposes a bidirectional channel delay measurement method based on MQTT (Message Queuing Telemetry Transport). It can effectively evaluate the real-time performance of communication links, considering that resources mainly access the grid through the public network. Subsequently, focusing on two typical types of resources on the demand side, namely, split air conditioners and central air conditioners, this article proposes an assessment method for correcting the response capabilities of air conditioning resources considering communication latency. Experimental simulations are conducted, and the results demonstrate that under given communication conditions, this method can more accurately estimate the response capability of air conditioners. This provides a basis for formulating more reasonable scheduling strategies, avoiding excessive or insufficient resource regulation caused by communication issues, and aiding the power grid in achieving precise scheduling. [ABSTRACT FROM AUTHOR]

As the Internet of Things (IoT) continues to proliferate, the demand for efficient and secure data processing at the network edge has grown exponentially. Fog computing, a paradigm that extends cloud capabilities to the edge of the network, plays a pivotal role in meeting these requirements. In this context, the reliable and trustworthy forwarding of data is of paramount importance. This paper presents an innovative mechanism designed to ensure the trustworthiness of data forwarding in the context of MQTT (Message Queuing Telemetry Transport), a widely adopted IoT communication protocol. Our proposed mechanism leverages the inherent advantages of MQTT to establish a robust and secure data-forwarding scheme. It integrates fog computing resources seamlessly into the MQTT ecosystem, enhancing data reliability and security. The mechanism employs trust models to evaluate the credibility of IoT devices and fog nodes involved in data forwarding, enabling informed decisions at each stage of the transmission process. Key components of the mechanism include secure communication protocols, authentication mechanisms, and data integrity verification. The proposed secure communication protocols (TLS/SSL, MQTTS, and PKI) and data integrity verification methods (MAC, digital signatures, checksums, and CRC) provide a robust framework for ensuring secure and trustworthy data transmission in IoT systems. These elements collectively contribute to the establishment of a reliable data forwarding pipeline within MQTT. Additionally, the mechanism prioritizes low-latency communication and efficient resource utilization, aligning with the real-time requirements of IoT applications. Through empirical evaluations and simulations, the research demonstrates the effectiveness of our proposed mechanism in improving the trustworthiness of data forwarding, while minimizing overhead, as the experiment was conducted with 15 fog nodes, and the maximum Level of Trust (LoT) score was 0.968, which is very high, with an estimated accuracy of 97.63%. The results indicate that our approach significantly enhances data security and reliability in MQTT-based IoT environments, thereby facilitating the seamless integration of fog computing resources for edge processing. [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]

Ensuring accountability and integrity in MQTT communications is important for enabling several IoT applications. This paper presents a novel approach that combines blockchain technology and the interplanetary file system (IPFS) to achieve non-repudiation and data integrity in the MQTT protocol. Our solution operates in discrete temporal rounds, during which the broker constructs a Merkle hash tree (MHT) from the messages received. Then the broker publishes the root on the blockchain and the MHT itself on IPFS. This mechanism guarantees that both publishers and subscribers can verify the integrity of the message exchanged. Furthermore, the interactions with the blockchain made by the publishers and the broker ensure they cannot deny having sent the exchanged messages. We provide a detailed security analysis, showing that under standard assumptions, the proposed solution achieves both data integrity and accountability. Additionally, we provided an experimental campaign to study the scalability and the throughput of the system. Our results show that our solution scales well with the number of clients. Furthermore, from our results, it emerges that the throughput reduction depends on the integrity check operations. However, since the frequency of these checks can be freely chosen, we can set it so that the throughput reduction is negligible. Finally, we provided a detailed analysis of the costs of our solution showing that, overall, the execution costs are relatively low, especially given the critical security and accountability benefits it guarantees. Furthermore, our analysis shows that the higher the number of subscribers in the system, the lower the costs per client in our solution. Again, this confirms that our solution does not present any scalability issues. [ABSTRACT FROM AUTHOR]

Copyright of GeSec: Revista de Gestao e Secretariado is the property of Sindicato das Secretarias e Secretarios do Estado de Sao Paulo (SINSESP) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The implementation of a Location Service for Emergency Medical Services system (LS4EMSs) is the goal of this study. by integration of pgRouting algorithm, Web Map Application, and Geo-IoT devices. The study is divided into 2 parts: (1) design of a security emergency incident location alarm system that can be used to track security emergencies in real time using Geo-IoT and (2) development of Emergency Routing Service (ERS) system based on web map application. NodeMCU ESP8266 and U-blox Neo-6 m GPS module were used for implementing Geo-IoT which can connect to Wi-Fi and give information including the location of the push button triggered by an individual in an emergency. ERS can determine the best route to take from the hospital or closest ambulance to the location where the Geo-IoT device is located. Free and Open-Source Software for Geospatial (FOSS4G) stack was used in the system's development, since it is easily adaptable to cover different purposes, including fire, flood, or other transport movements. The Integration of Geo-IoT and Web Routing Service for LS4EMSs improves utility as it is a near real-time ERS system. [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]

Air quality is a pressing global concern, resulting in millions of premature deaths annually. Accurate monitoring is vital to assess pollutant levels against established standards. Real-time systems are crucial in addressing air pollution challenges. This study aims to create a cost-effective, energy-efficient real-time air quality monitoring system using LPWAN (LoRa and NB-IoT) and MQTT for data collection. Implementing LoRa, this work highlight the significance of the local environment on transmission stability, including obstacles, elevation, and distance. Despite these factors, LoRa remains functional up to 1.65 km. Comparatively, LoRa excels for diverse applications, while NB-IoT suits areas with limited network coverage. [ABSTRACT FROM AUTHOR]

Nowadays, in the most developed countries, modern society is moving towards scenarios in which the self-sufficiency elderly people live alone in their homes. An automatic remote monitoring system using wearable sensors is becoming even more important in Ambient Assisted Living applications. For this type of services, it is important that IoT sensors networks, which are generally composed of devices with limited computing power and storage, implement reliable communication among sensors and the Internet. There are several specialized protocols for the Internet of Things proposed by the scientific community, each characterized by its own levels of Quality of Services. The emergence of new protocols forces the need for developing proxying systems able to intermediate among different types of networks and to translate the relative protocols. In this paper, we propose a complete architecture for monitoring and managing wearable devices, and, in particular, fall detection ones. Our system uses a cross protocol proxy and a device with CoAP and MQTT as application level protocols, while it exploits the NB-IoT at physical and data-link levels. The goal of this work is the performance evaluation of the proposed solution in terms of Throughput, Round Trip Time and Delay. The results highlight the low latency reached by the proposed system architecture thanks to the implemented protocols. [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]

Copyright of Iraqi Journal of Science is the property of Republic of Iraq Ministry of Higher Education & Scientific Research (MOHESR) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

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]

This paper aims to enhance security in IoT device networks through a visual tool that utilizes three projection techniques, including Beta Hebbian Learning (BHL), t-distributed Stochastic Neighbor Embedding (t-SNE) and ISOMAP, in order to facilitate the identification of network attacks by human experts. This work research begins with the creation of a testing environment with IoT devices and web clients, simulating attacks over Message Queuing Telemetry Transport (MQTT) for recording all relevant traffic information. The unsupervised algorithms chosen provide a set of projections that enable human experts to visually identify most attacks in real-time, making it a powerful tool that can be implemented in IoT environments easily. [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]

In pursuit of advancing fault diagnosis in electromechanical systems, this research focusses on vibration analysis through innovative techniques. The study unfolds in a structured manner, beginning with an introduction that situates the research question in a broader context, emphasising the critical role of fault diagnosis. Subsequently, the methods section offers a concise summary of the primary techniques employed, highlighting the utilisation of short-time Fourier transform (STFT) and continuous wavelet transform (CWT) for extracting time–frequency components from the signal. The results section succinctly summarises the main findings of the article, showcasing the results of features extraction by CWT and subsequently utilising a convolutional neural network (CNN) for fault diagnosis. The proposed method, named CWTx6-CNN, was compared with the STFTx6-CNN method of the previous stage of the investigation. Visual insights into the time–frequency characteristics of the inertial measurement unit (IMU) data are presented for various operational classes, offering a clear representation of fault-related features. Finally, the conclusion section underscores the advantages of the suggested method, particularly the concentration of single-frequency components for enhanced fault representation. The research demonstrates commendable classification performance, highlighting the efficiency of the suggested approach in real-time scenarios of fault analysis in less than 50 ms. Calculation by CWT with a complex Morlet wavelet of six time–frequency images and combining them into a single colour image took less than 35 ms. In this study, interpretability techniques have been employed to address the imperative need for transparency in intricate neural network models, particularly in the context of the case presented. Notably, techniques such as Grad-CAM (gradient-weighted class activation mapping), occlusion, and LIME (locally interpretable model-agnostic explanation) have proven instrumental in elucidating the inner workings of the model. Through a comparative analysis of the proposed CWTx6-CNN method and the reference STFTx6-CNN method, the application of interpretability techniques, including Grad-CAM, occlusion, and LIME, has played a pivotal role in revealing the distinctive spectral representations of these methodologies. [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]

In the burgeoning domain of electric vehicle (EV) technology, advancing supportive ecosystems is pivotal. There is a marked global uptrend in the adoption of EVs, necessitating a robust network of EV charging stations. The infrastructure and accompanying systems that govern these stations are integral to these stations. Increased utilization escalates the exigency for expeditious service at these charging points. This study undertakes a comparative analysis of three distinct data communication protocols at the application layer, specifically within the context of EV charging stations. The protocols scrutinized include Hypertext Transfer Protocol (HTTP), Message Queuing Telemetry Transport (MQTT), and Websocket. The benchmark for data transmission in this investigation is the delivery of energy information, adhering to the Open Charge Point Protocol (OCPP), a legally standardized open protocol. The data format employed is JavaScript Object Notation (JSON). Data transmission utilizing the three protocols above was intercepted and analyzed using Wireshark, a network protocol analyzer. Parameters such as latency (delay), jitter (variability of latency), and throughput (successful data delivery over a communication channel) were meticulously examined and subsequently represented graphically to enhance the interpretability of the network protocol performance. Despite identical data payloads, the findings reveal distinct transmission characteristics for each protocol. HTTP exhibited superior throughput, peaking at 31,621 bits per second (bps) during real-time data transmission. Conversely, MQTT demonstrated the most favorable latency and jitter metrics, both for real-time and periodic data dispatches. Websocket, however, registered the lowest throughput in real-time transmission, at 4,941 bps. These divergences underscore the importance of protocol selection based on specific performance criteria within EV charging station ecosystems. [ABSTRACT FROM AUTHOR]

Goal: Industrial operations are complex, and data sensors assure safety and reliable information for production improvements. Multiple stakeholders can take advantage of data acquisition for post-analysis and process control. Providing users and systems with friendly access to operating data is fundamental to the digital transition in the industry 4.0 scenario. Linking data and systems over ontologies and Industry Foundation Classes will boost supply chain performance in many layers. This paper presents the concept of valid data points over Uniform Resource Identifiers for sensor time-series into triples stores via Application Programming Interfaces. Design/Methodology/Approach: A streaming data source approach to integrating industrial sensor data and sharing it via Uniform Resource Identifiers is developed and tested using Node-Red with multiple data connection types, such as the Industry Foundation Classes and open-source time series databases. Results: The detailed proof of concept presented valid the feasibility of sharing sensor data via Uniform Resource Identifiers. The findings provide a backbone of a system able to interop Message Queuing Telemetry Transport data, Resource Description Framework datasets and Industry Foundation Classes schema. Limitations of the investigation: The system envisaged was tested using simulated data. However, it is expected to have similar results from real data use. Nevertheless, more research will be needed to implement more features, such as three-dimensional object integration. Practical implications: The solution designed and tested presented can be used in practice for companies that desire to expand via linked data shareability and interoperability. Also, researchers can advance the solution for specific features, such as creating an open-source data query and manipulation language. Originality/Value: This paper examines future deployments of systems-to-systems interoperability targeting user-friendly data shareability. It is meant to be useful for industrial and academic developments. [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]

MQTT, a popular IoT messaging protocol, is frequently associated with numerous vulnerabilities, the majority of which are critical. Many IoT devices that utilize MQTT are susceptible to cyberattacks such as denial-of-service and buffer overflow. In this paper, we unveil a novel Denial of Service (DoS) attack in the MQTT protocol, referred to as Slow Subscribers, which has the potential to cause MQTT brokers to become single points of failure. Unlike existing MQTT DoS attacks, Slow Subscribers can occur on a single compromised node and could potentially disrupt a MQTT broker with minimal subscription permissions. We evaluated the reliability of Mosquitto and NanoMQ, two popular MQTT messaging brokers, to determine the effect of Slow Subscribers. According to the findings of our investigation, NanoMQ outperforms Mosquitto in response to the Slow Subscribers attack at QoS level 0. We also determine that the response to Slow Subscribers at QoS 2 is the worst for both broker implementations. In addition, the results of our experiments indicate that Eclipse Mosquitto achieves a higher rate of reliability than NanoMQ on cloud deployments whereas NanoMQ has proven to be well-suited for edge environments, especially edge IoT devices that require the use of QoS levels 0 and 1. Finally, we propose a Resilient Middleware for Message Queue Telemetry Transport (Remistry) framework that is capable of detecting misconfigurations while providing granular support of resource commitment errors, in particular the out-of-memory (OOM) problems for effectively mitigating the impact of Slow Subscribers attacks on MQTT brokers. [ABSTRACT FROM AUTHOR]

The Internet-of-Things concept has evolved from providing network connectivity for devices in our physical world to composing complex tasks with the representations of these things in service mashups. Since most of these devices (e.g. wireless sensors, tagged objects) are resource-constrained, it is easy to realize that such objects provide basic services individually and thus, motivates the need to aggregate such services for complex tasks. However, the existence of fragmentation in protocols and standards for device management and service enablement has been a challenge for the domain. In this work, we propose a resource-oriented device management and service enablement architecture that addresses this problem. We also present a smart home application scenario to demonstrate the performance and feasibility of our approach. [ABSTRACT FROM AUTHOR]

Message Queuing Telemetry Transport (MQTT) enables asynchronous confirmation of message reception by brokers but lacks a way for publishers to know when subscribers receive their messages without adding additional communication overhead. This paper addresses this problem by improving MQTT to establish end-to-end communication between a publisher and subscribers, reducing message exchanges, using what is called End-to-End MQTT (E-MQTT). In E-MQTT, a publisher sets the number of responses that it will wait for when it sends a message. After the broker collects the response messages from subscribers, it sends one aggregated response back to the publisher. The publisher also can receive the response message synchronously or asynchronously. Experimental results consistently show that E-MQTT outperforms traditional MQTT in terms of delay, especially when the publisher needs to monitor when its query message is received by subscribers. Although E-MQTT packets are slightly larger due to additional fields, the difference in packet size compared to MQTT is not significant. [ABSTRACT FROM AUTHOR]

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]

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]

As the importance of smart factories has recently been emphasized in industrial settings, the use of industrial networks is increasing. Accordingly, research was conducted on Edge Gateway, which collects data generated from equipment at industrial sites and transmits it to a cloud server. However, Edge Gateway studies require additional I/O to be installed in the industrial network to receive status information generated from manufacturing devices. This may result in increased network communication cycles and modification of PLC programs, which can result in budget and time consumption. Accordingly, in this paper, the solution is to add I/O to the Edge Gateway device to minimize PLC program modification without installing additional I/O in the industrial network. According to the experimental results, adding distributed I/O to the network resulted in an increase in cycle time of up to 0.24ms in the communication cycle, and showed an increase in cycle time of up to 8.41%. [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]

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]

The prevalence of Internet of Things (IoT) systems deployment is increasing across various domains, from residential to industrial settings. These systems are typically characterized by their modest computational requirements and use of lightweight communication protocols, such as MQTT. However, the rising adoption of IoT technology has also led to the emergence of novel attacks, increasing the susceptibility of these systems to compromise. Among the different attacks that can affect the main IoT protocols are Denial of Service attacks (DoS). In this scenario, this paper evaluates the performance of six supervised classification techniques (Decision Trees, Multi-layer Perceptron, Random Forest, Support Vector Machine, Fisher Linear Discriminant and Bernoulli and Gaussian Naive Bayes) combined with the Principal Component Analysis (PCA) feature extraction method for detecting DoS attacks in MQTT networks. For this purpose, a real dataset containing all the traffic generated in the network and many attacks executed has been used. The results obtained with several models have achieved performances above 99% AUC. [ABSTRACT FROM AUTHOR]

The government has supported the development of freshwater fisheries or local fisheries via the Fisheries Statistics Group, Fisheries Development Policy and Planning Division of the Department of Fisheries. In the development of local areas, freshwater fishing is encouraged for a group of 3 species of fish: Tilapia, Catfish and Tapia. The problems encountered by freshwater fisheries are water quality and feeding procedures in freshwater fisheries that provide food with not actual proportional. Consequently there are increasing labor costs and deteriorating water quality. We found a way to manage fish feeding automatically and check water quality through the application of MQT technology to manage work and to monitor the data to suit freshwater fishing, providing quality of growth and proper control of the amount of food supplied, thereby reducing food costs. The research was divided into two parts: hardware and software. Hardware was an M.C.U. node with a relay used to control the motor. In addition, there was a PH sensor module and waterproof temperature sensor. Python programming served as a platform for developing applications used to communicate with users. The results showed that Farmers were satisfied because the good quality of water provided survival rates of catfish in the nursery which increased from the original 92% to 100% after the trial and also reduced the labor cost of taking care of the nursery catfish for 1,725 baht/month. This was possible because information can be checked and controlled through an application as can the remaining time for other occupations. [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]

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]

This paper proposes a general and interoperable Web of Things (WoT)-oriented architecture to support a distributed storage application. In particular, the focus is on a distributed ledger service dedicated to machine-to-machine (M2M) transactions occurring in an intelligent ecosystem. For this purpose, the basic functional modules have been characterized and integrated into a comprehensive framework relying on an IOTA approach. Furthermore, a general protocol that is built upon an underlying publish-and-subscribe framework is proposed to support all the application phases. The proposed approach has been validated by a simulation campaign targeting the achievable latency and throughput and, further, by a qualitative analysis of high-level metrics, both pointing out several advantages in terms of interoperability, scalability, and mobility support, together with addressing some constraints affecting service availability and security. [ABSTRACT FROM AUTHOR]

The Internet of Things (IoT) deployment in emerging markets has increased dramatically, making security a prominent issue in IoT communication. Several protocols are available for IoT communication; among them, Message Queuing Telemetry Transport (MQTT) is pervasive in intelligent applications. However, MQTT is designed for resource-constrained IoT devices and, by default, does not have a security scheme, necessitating an additional security scheme to overcome its weaknesses. The security vulnerabilities in MQTT inherently lead to overhead and poor communication performance. Adding a lightweight security framework for MQTT is essential to overcome these problems in a resource-constrained environment. The conventional MQTT security schemes present a single trusted scheme and perform attribute verification and key generation, which tend to be a bottleneck at the server and pave the way for various security attacks. In addition to that, using the same secret key for an extended period and a flawed key revocation system can affect the security of MQTT. To address these issues, we propose an Improved Ciphertext Policy-Attribute-Based Encryption (ICP-ABE) integrated with a lightweight symmetric encryption scheme, PRESENT, to improve the security of MQTT. In this work, the PRESENT algorithm enables the secure sharing of blind keys among clients. We evaluated a previously proposed ICP-ABE scheme from the perspective of energy consumption and communication overhead. Furthermore, we evaluated the efficiency of the scheme using provable security and formal methods. The simulation results showed that the proposed scheme consumes less energy in standard and attack scenarios than the simple PRESENT, Key Schedule Algorithm (KSA)-PRESENT Secure Message Queue Telemetry Transport (SMQTT), and ECC-RSA frameworks, with a topology of 30 nodes. In general, the proposed lightweight security framework for MQTT addresses the vulnerabilities of MQTT and ensures secure communication in a resource-constrained environment, making it a promising solution for IoT applications in emerging markets. [ABSTRACT FROM AUTHOR]

A low-cost embedded system for high-energy radiation detection applications was developed for national security proposes, mainly to detect nuclear material and send the detection event to the cloud in real time with tracking capabilities. The proof of concept was built with state-of-the-art electronics such as an adequate Si-based photodetector, a trans-impedance amplifier, an ARM Cortex M4 microcontroller with sufficient ADC capture capabilities, an ESP8266 Internet of Things (IoT) module, an optimized Message Queuing Telemetry Transport (MQTT) protocol, a MySQL data base, and a Python handler program. The system is able to detect alfa particles and send the nuclear detection events to the CloudMQTT servers. Moreover, the detection message records the date and time of the ionization event for the tracking application, and due to a particular MQTT-optimized protocol the message is sent with low latency. Furthermore, the designed system was validated with a standard radiation instrumentation preamplifier 109A system from ORTEC company, and more than one node was demonstrated with an internet connection employing a 20,000 bits/s CloudMQTT plan. Therefore, the design can be escalated to produce a robust big data multisensor network. [ABSTRACT FROM AUTHOR]