Search

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]

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]

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]

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]

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]

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]

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]

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 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]

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]

The paper presents a new and innovative decision support system for electric arc furnace operators to optimise the process control efficiency. The system combines two tools, the EAF Simulator and EAF Optimiser, which contain advanced mechanistic and data-driven models. They have been trained using historical data and allow simulation of planned batches with real-time data. This provides operators with valuable information on how to adjust furnace settings. The main feature of the system is the intuitive graphical interface implemented in the Siemens MindSphere environment and Node- RED, which enables interactive analysis and management. The inter-face allows operators to analyse historical batches and compare them with simulations, as well as adjust various input data and melting parameters. Furthermore, the tools added benefit of being able to determine the optimal furnace settings to optimise the process and reduce operating costs, particularly energy consumption. The decision support system is a powerful digital twin that helps electric arc furnace operators make decisions and leads to more sustainable and efficient operations. [ABSTRACT FROM AUTHOR]

MQ Telemetry Transport (MQTT) has been designed and developed for an ultra-low bandwidth communication and has been applied to used in Internet of Things (IoT). Recently, MQTT has been used in traditional TCP/IP networks. Yet, the ultra-low bandwidth and long-range communication of MQTT have been considerably increased. Previous proposed techniques still struggle to make MQTT compatible with Long-Range (LoRa) networks. In this paper, we have design and implement the Telemetry Media Access Control (TMAC). Our TMAC helps increase ranges of MQTT's data communications. We have experimented our TMAC using a network testbed. Experimental results have illustrated that our TMAC can transfer data over 5 kilometers with low network overhead. [ABSTRACT FROM AUTHOR]

The Internet of things (IoT) accommodates lightweight sensor/actuator devices with limited resources; hence, more efficient methods for known challenges are sought after. Message queue telemetry transport (MQTT) is a publish/subscribe-based protocol that allows resource-efficient communication among clients, so-called brokers, and servers. However, it lacks viable security features beyond username/password checks, yet transport-layer security (TLS/HTTPS) is not efficient for constrained devices. MQTT also lacks mutual authentication among clients and brokers. To address the issue, we developed a mutual authentication and role-based authorization scheme for lightweight Internet of things applications (MARAS). It brings mutual authentication and authorization to the network via dynamic access tokens, hash-based message authentication code (HMAC)-based one-time passwords (HOTP), advanced encryption standard (AES), hash chains, and a trusted server running OAuth2.0 along with MQTT. MARAS merely modifies "publish" and "connect" messages among 14 message types of MQTT. Its overhead to "publish" messages is 49 bytes, and to "connect" messages is 127 bytes. Our proof-of-concept showed that the overall data traffic with MARAS remains lower than double the traffic without it, because "publish" messages are the most common. Nevertheless, tests showed that round-trip times for a "connect" message (and its "ack") are delayed less than a percentile of a millisecond; for a "publish" message, the delays depend on the size and frequency of published information, but we can safely say that the delay is upper bounded by 163% of the network defaults. So, the scheme's overhead to the network is tolerable. Our comparison with similar works shows that while our communication overhead is similar, MARAS offers better computational performance as it offloads computationally intensive operations to the broker side. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) paved the way for devices and machine communication using TCP/IP protocol. Lightweight and stateless communication is imperative especially in a situation requiring conservation of energy usage, e.g. wireless sensor network. Representational State Transfer (REST) API method is based on web communication protocol, Hyper-Text Transfer Protocol (HTTP), and is widely used in IoT messaging. Some of these protocols are DPWS, XMPP, MQTT, COaP, AMQP. Among these protocols, MQTT is the most preferred protocol and is expected to be the de facto messaging IoT standard. MQTT uses a publisher/subscriber model to facilitate messaging between devices making messaging lightweight. Nevertheless, there are a number of security issues due to the design of the protocol itself. Some of the issues are denial of service, identity spoofing, information disclosure, elevation of privileges and data tampering. These issues can be caused by both internal and external perpetrators. Researchers have proposed various security techniques and mechanisms to address these issues. Incorporation of security has added processing overhead to the devices and this will have a bearing on IoT devices that are powered by a battery. This issue has opened up new research challenges in making the protocols more lightweight and at the same time not compromising the level of security provided. [ABSTRACT FROM AUTHOR]

Unmanned aerial vehicle based precision agriculture is a predominant research area. The modern flying ad‐hoc network leverages the advanced low latency vehicular communication and intelligent computing paradigms that help the ecosystem to grow up to the next level. In this work, we propose an ecosystem for precision agriculture that leverages the use of the opportunistic MQTT protocol in an edge‐enabled intelligent drone network for sensing and performing crop prediction using an intelligent ensemble machine learning model. The proposed approach leverages the edge computing system that requires low energy devices and also exploits the ultra‐low latency opportunistic message transfer methodology. The experimental results show the maximum of 0.9 message delivery ratio and a minimum of 600 ms latency is achieved by opportunistic MQTT protocol in an ultra‐low latency sparse network scenario. A weighted ensemble model is deployed onto the edge enabled devices or the drones. An accuracy of 96.5% is achieved in predicting the type of crops that can be grown in the soil about the selected area of interest. [ABSTRACT FROM AUTHOR]

Smart objects and home automation tools are becoming increasingly popular, and the number of smart devices that each dedicated application has to manage is increasing accordingly. The emergence of technologies such as serverless computing and dedicated machine-to-machine communication protocols represents a valuable opportunity to facilitate management of smart objects and replicability of new solutions. The aim of this paper is to propose a framework for home automation applications that can be applied to control and monitor any appliance or object in a smart home environment. The proposed framework makes use of a dedicated messages-exchange protocol based on MQTT and cloud-deployed serverless functions. Furthermore, a vocal command interface is implemented to let users control the smart object with vocal interactions, greatly increasing the accessibility and intuitiveness of the proposed solution. A smart object, namely a smart kitchen fan extractor system, was developed, prototyped, and tested to illustrate the viability of the proposed solution. The smart object is equipped with a narrowband IoT (NB-IoT) module to send and receive commands to and from the cloud. In order to evaluate the performance of the proposed solution, the suitability of NB-IoT for the transmission of MQTT messages was evaluated. The results show how NB-IoT has an acceptable latency performance despite some minimal packet loss. [ABSTRACT FROM AUTHOR]

A new medical cryptosystem based on four chaotic maps is presented as a case study. The message queuing telemetry transport (MQTT) protocol is used in this research to propose an end-to-end chaotic encryption technique that would enhance security and secrecy to the transmission of medical images from any Healthcare Internet of Things (H-IoT) device connected to the Internet. The maximal Lyapunov exponent (LE), the analysis of bifurcation diagrams, the Statistical Test Suit from the National Institute of Standard and Technology in the Special Publication 800–22 (NIST SP 800–22), and TestU01 statistical tests are used to evaluate the randomness of the sequences. The proposed medical image encryption technique is confirmed to be strong enough to withstand most current assaults, including differential attacks, the correlation between adjacent pixels, statistical histograms, entropy, key-space, and key-space attacks. The suggested cryptosystem is suitable for edge computing devices and has throughputs of up to 10.53 Mbit/s on a Raspberry Pi 4 (RPi4) and 47.44 Mbit/s utilizing a 2.9 GHz CPU on a desktop PC with improved sequences from the Logistic 1D map. Because of this, the proposed embedded medical cryptosystem may be used to strengthen the security of real-time medical image transmission across WiFi networks and the Internet. • This paper presents a real-time medical image encryption using four chaotic maps and post-processing by using mod 1023 function. • The improved chaotic sequences using mod 1023 are tested by encrypting different medical images in grayscale and RGB format. • A wireless communication scheme on a M2M link, via WIFI channels, and over the internet using the MQTT protocol. • The proposed scheme presents high security and robustness against cryptanalysis. • Security analysis verifies the effectiveness of the encryption scheme for novel H-IoT applications operating in real time. [ABSTRACT FROM AUTHOR]

The human-centric and resilient European industry called Industry 5.0 requires a long lifetime of machines to reduce electronic waste. The appropriate way to handle this problem is to apply a diagnostic system capable of remotely detecting, isolating, and identifying faults. The authors present usage of HTTP/1.1 protocol for batch processing as a fault diagnosis server. Data are sent by microcontroller HTTP client in JSON format to the diagnosis server. Moreover, the MQTT protocol was used for stream (micro batch) processing from microcontroller client to two fault diagnosis clients. The first fault diagnosis MQTT client uses only frequency data for evaluation. The authors' enhancement to standard fast Fourier transform (FFT) was their usage of sliding discrete Fourier transform (rSDFT, mSDFT, gSDFT, and oSDFT) which allows recursively updating the spectrum based on a new sample in the time domain and previous results in the frequency domain. This approach allows to reduce the computational cost. The second approach of the MQTT client for fault diagnosis uses short-time Fourier transform (STFT) to transform IMU 6 DOF sensor data into six spectrograms that are combined into an RGB image. All three-axis accelerometer and three-axis gyroscope data are used to obtain a time-frequency RGB image. The diagnosis of the machine is performed by a trained convolutional neural network suitable for RGB image recognition. Prediction result is returned as a JSON object with predicted state and probability of each state. For HTTP, the fault diagnosis result is sent in response, and for MQTT, it is send to prediction topic. Both protocols and both proposed approaches are suitable for fault diagnosis based on the mechanical vibration of the rotary machine and were tested in demonstration. [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. [ABSTRACT FROM AUTHOR]

Device-free localization (DFL) systems exploit changes in the radio frequency channel by measuring, for example, the channel impulse response (CIR), to detect and localize obstacles within a target area. However, due to a lack of well-defined interfaces, missing modularization, as well as complex system configuration, it is difficult to deploy DFL systems outside of laboratory setups. This paper focused on the system view and the challenges that come with setting up a DFL system in an indoor environment. We propose MA-RTI, a modular DFL system that is easy to set up, and which utilizes a multipath-assisted (MA) radio-tomographic imaging (RTI) algorithm. To achieve a modular DFL system, we proposed and implemented an architectural model for DFL systems. For minimizing the configuration overhead, we applied a 3D spatial model, that helps in placing the sensors and calculating the required calibration parameters. Therefore, we configured the system solely with idle measurements and a 3D spatial model. We deployed such a DFL system and evaluated it in a real-world office environment with four sensor nodes. The radio technology was ultra-wideband (UWB) and the corresponding signal measurements were CIRs. The DFL system operated with CIRs that provided a sub-nanosecond time-domain resolution. After pre-processing, the update rate was approximately 46 Hz and it provided a localization accuracy of 1.0 m in 50% of all cases and 1.8 m in 80% of all cases. MA fingerprinting approaches lead to higher localization accuracy, but require a labor-intensive training phase. [ABSTRACT FROM AUTHOR]

Due to the recent advances in the domain of smart agriculture as a result of integrating traditional agriculture and the latest information technologies including the Internet of Things (IoT), cloud computing, and artificial intelligence (AI), there is an urgent need to address the information security-related issues and challenges in this field. In this article, we propose the integration of lightweight cryptography techniques into the IoT ecosystem for smart agriculture to meet the requirements of resource-constrained IoT devices. Moreover, we investigate the adoption of a lightweight encryption protocol, namely, the Expeditious Cipher (X-cipher), to create a secure channel between the sensing layer and the broker in the Message Queue Telemetry Transport (MQTT) protocol as well as a secure channel between the broker and its subscribers. Our case study focuses on smart irrigation systems, and the MQTT protocol is deployed as the application messaging protocol in these systems. Smart irrigation strives to decrease the misuse of natural resources by enhancing the efficiency of agricultural irrigation. This secure channel is utilized to eliminate the main security threat in precision agriculture by protecting sensors' published data from eavesdropping and theft, as well as from unauthorized changes to sensitive data that can negatively impact crops' development. In addition, the secure channel protects the irrigation decisions made by the data analytics (DA) entity regarding the irrigation time and the quantity of water that is returned to actuators from any alteration. Performance evaluation of our chosen lightweight encryption protocol revealed an improvement in terms of power consumption, execution time, and required memory usage when compared with the Advanced Encryption Standard (AES). Moreover, the selected lightweight encryption protocol outperforms the PRESENT lightweight encryption protocol in terms of throughput and memory usage. [ABSTRACT FROM AUTHOR]

Abrupt collapse events that result in casualties due to failure of load-bearing structures have been reported in recent years. Continuous remote monitoring of these structures, assessing the behavior under operational load, could provide a reliable prevention, as the developing damage manifests itself through a loss of stiffness, and therefore excessive deflections. Digital image correlation (DIC) algorithms based on fast Fourier transform (FFT) were implemented in a small computer unit Raspberry Pi, capable of remote operation in a low-energy demand mode. The unit is fully autonomous, capable of localizing QR code targets and extracting encoded information. This strategy allows us to instantly evaluate displacements of QR codes attached to any surface and send the data to a server. The software was developed in Python, allowing for two modes: the online mode for current data evaluation with information transfer via the MQTT protocol and the offline mode used for retrospective evaluation. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Internet of Things (IoT) networks are becoming increasingly popular for monitoring critical environments of various types. For the communication of IoT devices, several lightweight protocols have been developed. MQTT (message queuing telemetry transport) is a widely used messaging protocol in IoT using the publish–subscribe technique. The openness of publish–subscribe model and the limited built-in authentication capabilities makes it vulnerable to intruders. Hence, an intrusion detection system (IDS) has a vital role in MQTT-IoT security. This paper proposes an efficient intrusion detection mechanism for the MQTT-IoT networks using an enhanced chaotic salp swarm optimization algorithm (ECSSA) and LightGBM classifier. Traditional IDS uses a lot of irrelevant data and undesirable attributes, resulting in long detection times and low performance. To overcome the limitations, the proposed IDS uses ECSSA for feature selection and LightGBM classifier for better detection accuracy. The experimental verification on MC-IoT, MQTT-IoT-IDS2020, and MQTTset datasets demonstrates that ECSSA and LightGBM improve the overall accuracy rate. The proposed technique outperforms the existing approaches with an accuracy of 99.38%, 98.91%, and 98.35% in the three test sets, MC-IoT, MQTT-IoT-IDS2020, and MQTTset, respectively. [ABSTRACT FROM AUTHOR]

Internet of Things and wireless sensor network applications are becoming more and more popular these days, supported by new communication technologies and protocols tailored to their specific requirements. This paper focuses on improving the performance of a Wireless Sensor Network operated by the MQTT-SN protocol, one of the most popular publish/subscribe protocols for IoT applications. In particular, we propose a dynamic Quality of Service (QoS) controller for the MQTT-SN protocol, capable of evaluating the status of the underlying network in terms of end-to-end delay and packet error rate, reacting consequently by assigning the best QoS value to a node. We design and implement the QoS controller in a simulated environment based on the ns-3 network emulator, and we perform extensive experiments to prove its effectiveness compared to a non-controlled scenario. The reported results show that, by controlling the quality of service, it is possible to effectively manage the number of packets successfully received by each device and their average latency, to improve the quality of the communication of each end node. [ABSTRACT FROM AUTHOR]

Routing is a key to exchange of the messages between the IoT enabled devices. For routing to be effective and efficient the message needs to be delivered instantly between neighboring nodes in IoT enabled network, if they are co-located in the overlapping transmission range of each other or through the cloud if the devices are located remotely. In today's scenario, optimized routing is the need of the hour. In the proposed research work, an effort has been made to demonstrate the effective routing between publisher and subscriber through a centralized broker using IoT routing protocol such as MQTT (Message Queue Telemetry Transport). The Simulation of the protocol has been accomplished in JAVA Programming language using MOSQUITTO open-source toolkit and the results have been positive and encouraging. [ABSTRACT FROM AUTHOR]

Industrial IoT is a crucial domain of Industry 4.0. Automation and computational methods are helpful for industrial IoT systems. As IoT systems are protocol communication-centric systems, it is necessary to provide security analysis systems. In the case of pharmaceutical industrial automation, many times for hazardous chemical plants, machine-to-machine, and machine-to-sensor systems are considered better. However, IoT middleware systems need to be secure regarding protocol communication. Many IIoT systems generally use MQTT and CoAP protocols. Hence, this paper presents the process execution framework for identifying possible attacks where the delay is the critical parameter. Like a decision tree, the machine learning algorithm can immediately provide the decision for requests and responses received from any sensor and machine. The proposed research can be used for other industries commissioned by IoT systems. [ABSTRACT FROM AUTHOR]

Message Queuing Telemetry Transport (MQTT) is a lightweight publish/subscribe protocol, which is currently one of the most popular application protocols in Internet of Things (IoT) thanks to its simplicity in use and its scalability. The secured version, MQTTS, which combines MQTT with the Transport Layer Security (TLS) protocol, has several shortcomings. It only offers one-to-one security, supports a limited number of security features and has high computation and communication costs. In this paper, we propose a flexible and lightweight security solution to be integrated in MQTT, addressing many-to-many communication, which reduces the communication overhead by 80% and the computational overhead by 40% for the setup of a secure connection on the client side. [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]

Nowadays, rapid developments of Internet of Things (IoT) technologies have increased possibilities of realizing smart cities where collaborations and integrations of various IoT application systems are essential. However, IoT application systems have often been designed and deployed independently without considering the standards of devices, logics, and data communications. In this paper, we present the design and implementation of the IoT server platform called Smart Environmental Monitoring and Analytical in Real-Time (SEMAR) for integrating IoT application systems using standards. SEMAR offers Big Data environments with built-in functions for data aggregations, synchronizations, and classifications with machine learning. Moreover, plug-in functions can be easily implemented. Data from devices for different sensors can be accepted directly and through network connections, which will be used in real-time for user interfaces, text files, and access to other systems through Representational State Transfer Application Programming Interface (REST API) services. For evaluations of SEMAR, we implemented the platform and integrated five IoT application systems, namely, the air-conditioning guidance system, the fingerprint-based indoor localization system, the water quality monitoring system, the environment monitoring system, and the air quality monitoring system. When compared with existing research on IoT platforms, the proposed SEMAR IoT application server platform offers higher flexibility and interoperability with the functions for IoT device managements, data communications, decision making, synchronizations, and filters that can be easily integrated with external programs or IoT applications without changing the codes. The results confirm the effectiveness and efficiency of the proposal. [ABSTRACT FROM AUTHOR]

With the fast and unstoppable development of technology, the amount of available technological devices and the data they produce is overwhelming. In analyzing the context of a smart home, a diverse group of intelligent devices generating constant reports of its environment information is needed for the proper control of the house. Due to this demand, many possible solutions have been developed in the literature to assess the need for processing power and storage capacity. This work proposes HOsT (home-context-aware fog-computing solution)—a solution that addresses the problems of data heterogeneity and the interoperability of smart objects in the context of a smart home. HOsT was modeled to compose a set of intelligent objects to form a computational infrastructure in fog. A publish/subscribe communication module was implemented to abstract the details of communication between objects to disseminate heterogeneous information. A performance evaluation was carried out to validate HOsT. The results show evidence of efficiency in the communication infrastructure; and in the impact of HOsT compared with a cloud infrastructure. Furthermore, HOsT provides scalability about the number of devices acting simultaneously and demonstrates its ability to work with different devices. [ABSTRACT FROM AUTHOR]

Guaranteeing security in information exchange is a challenge in public networks, such as in the highly popular application layer Message Queue Telemetry Transport (MQTT) protocol. On the one hand, chaos generators have shown their usefulness in masking data that can be recovered while having the appropriate binary string. Privacy can then be accomplished by implementing synchronization techniques to connect the transmitter and receiver, among millions of users, to encrypt and decrypt data having the correct public key. On the other hand, chaotic binary sequences can be generated on Rapsberry Pis that can be connected over MQTT. To provide privacy and security, the transmitter and receiver (among millions of devices) can be synchronized to have the same chaotic public key to encrypt and decrypt data. In this manner, this paper shows the implementation of optimized chaos generators on Raspberry Pis that are wirelessly connected via MQTT for the IoT protocol. The publisher encrypts data that are public to millions of interconnected devices, but the data are decrypted by the subscribers having the correct chaotic binary sequence. The image encryption system is tested by performing NIST, TestU01, NPCR, UACI and other statistical analyses. [ABSTRACT FROM AUTHOR]

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%. [ABSTRACT FROM AUTHOR]

Adding connectivity to vehicles is attracting much attention toward developing smarter vehicles such as autonomous cars. To obtain and utilize real-time information from vehicles, techniques that combine the concept of edge computing and publish/subscribe messaging model have been proposed. However, there is an issue that the increase in the number of edge servers imposes a heavy load upon a subscriber for managing connections to them. To address this issue, we propose an edge-based platform with the functionality of adjusting the number of connections to edge servers. Experimental results clarify the trade-off characteristic between subscription load and latency. [ABSTRACT FROM AUTHOR]

This paper presents a novel solution in the field of the integration of the Smart Grid and the Internet of Things. The definition of a web platform able to offer a RESTful interface to IEC 61850 Servers to a generic user is proposed. The web platform enables the mapping of information maintained by an IEC 61850 Server into MQTT messages. Suitable mechanisms to introduce interoperable exchange of information were defined. The paper presents the main features offered by the proposed platform. The originality of the proposal is highlighted by comparing it with the current literature. A prototype was realized, and the software implementation choices are described and the main results of its evaluation are presented. [ABSTRACT FROM AUTHOR]

The hydroponic system is a method of growing plants without using soil but using water. Even without soil, plants can grow well because the essential nutrients provided through the nutrient solution (AB Mix) are sufficient. Nutrients in a hydroponic system needs to be monitored regularly so that plants can grow optimally and not lack or excess of nutrients. This research proposed a hydroponic monitoring system that can monitor the condition of hydroponic nutrients remotely in real time using MQTT protocol and Antares platform. The sensors that will be used are Total Dissolved Solid (TDS) sensor to determine the level of nutrients in the water, a DHT11 sensor to check the temperature and humidity around the hydroponic system, and ultrasonic sensor to measure the water level in the reservoir. The result of this system design is a device for monitoring hydroponic using the Antares platform. What was observed in this study was the nutrient content and water level in the reservoir with parameters of the ideal nutrient levels are in the range of 1050-1500 ppm, while the water level was in the range of 6-8 cm. The results of Quality of Service (QoS) test of the MQTT protocol obtained an average delay of 2.5 s and a throughput of 2099 bps. [ABSTRACT FROM AUTHOR]

This paper presents a scalable IoT architecture based on the edge–fog–cloud paradigm for monitoring the Indoor Environmental Quality (IEQ) parameters in public buildings. Nowadays, IEQ monitoring systems are becoming important for several reasons: (1) to ensure that temperature and humidity conditions are adequate, improving the comfort and productivity of the occupants; (2) to introduce actions to reduce energy consumption, contributing to achieving the Sustainable Development Goals (SDG); and (3) to guarantee the quality of the air—a key concern due to the COVID-19 worldwide pandemic. Two kinds of nodes compose the proposed architecture; these are the so-called: (1) smart IEQ sensor nodes, responsible for acquiring indoor environmental measures locally, and (2) the IEQ concentrators, responsible for collecting the data from smart sensor nodes distributed along the facilities. The IEQ concentrators are also responsible for configuring the acquisition system locally, logging the acquired local data, analyzing the information, and connecting to cloud applications. The presented architecture has been designed using low-cost open-source hardware and software—specifically, single board computers and microcontrollers such as Raspberry Pis and Arduino boards. WiFi and TCP/IP communication technologies were selected, since they are typically available in corporative buildings, benefiting from already available communication infrastructures. The application layer was implemented with MQTT. A prototype was built and deployed at the Faculty of Engineering of Vitoria-Gasteiz, University of the Basque Country (UPV/EHU), using the existing network infrastructure. This prototype allowed for collecting data within different academic scenarios. Finally, a smart sensor node was designed including low-cost sensors to measure temperature, humidity, eCO2, and VOC. [ABSTRACT FROM AUTHOR]

In recent years, while internet of things (IoT) devices and cloud computing environments have been penetrated, the increase in communication latency and concentration of traffic caused by data centers has deteriorated the quality of some network services. Message Queuing Telemetry Transport (MQTT) is a well‐known protocol for exchanging messages between dedicated applications. MQTT employs a publish–subscribe model in which a broker mediates communication between IoT devices and applications. To improve service quality, the processing latency of the broker should be reduced. Moreover, the broker's throughput must be increased. IoT devices, in particular, must maintain a highly accurate time to provide some IoT services. This study proposed hardware implementation of MQTT broker and evaluated the accuracy of an MQTT‐based time synchronization method. The proposed MQTT architecture's hardware resource utilization is also provided. We confirmed that our implementation achieved high throughput, low latency, and low jitter MQTT broker, which satisfies the smart city services for automated drive and power control, which must be less than a few milliseconds. © 2021 Institute of Electrical Engineers of Japan. Published by Wiley Periodicals LLC. [ABSTRACT FROM AUTHOR]

Deep learning methods have been gradually adopted in the Internet-of-Things (IoT) applications. Nevertheless, the large demands for the computation and memory resources make these methods difficult to be deployed in the field as the resource-constrained IoT devices would be overwhelmed by the computations incurred by the inference operations of the deployed deep learning models. In this article, we propose the adaptive computation framework, which is built on top of the distributed deep neural networks (DDNNs), to facilitate the inference computations of a trained DDNN model to be collaboratively executed by the machines in a distributed computing hierarchy, e.g., the end device and the cloud server. By facilitating the trained models to be run on the actual distributed systems, the proposed framework enables the co-design of the distributed deep learning models and systems, since the delivered performance of the models on the systems, in terms of the inference time, consumed energy and model accuracy, is able to be measured and is served as the input for the next cycle for the model/system design. We have built the surveillance system for the object detection application with the prototyped framework. We use the surveillance system as a case study to demonstrate the capabilities of the proposed framework. In addition, the design considerations of developing the DDNN system are shared. With the promising results presented in the article, we believe that the framework paves a road for the automated design process of the distributed deep learning models/systems. [ABSTRACT FROM AUTHOR]

The LoRa technology enables long distance links with reduced power consumption at low cost, the main limitation being the low bandwidth that it offers. With LoRa, remote locations, like rural areas, can benefit from connectivity based services that would otherwise be impossible. In this work, we describe a LoRa architecture that can include generic external data sources using an MQTT-based interface. We particularly focus on audio sources aiming to two basic services: a voice messaging system that allows users who cannot read or write to send voice notes, and an audio compression service to extract the main features from the audio input to use it for developing intelligent ML-based audio analytics. [ABSTRACT FROM AUTHOR]

The most prominent protocols for data transfer in internet of things (IoT) are message queuing telemetry transport (MQTT) and constrained application protocol (CoAP). The existing clients from both sides are unable to communicate directly because of the packet's header structure difference in application and transport layer. In response, this paper aims to develop a bidirectional conversion server used to translate the specified messaging protocol interchangeably in the OpenFlow network and transmit the converted packet from both sides. The conversion server integrated the MQTT subscriber and CoAP POST object for converting the MQTT message into CoAP data. Similarly, the CoAP-MQTT translation was processed by CoAP GET and MQTT publisher object. The research was evaluated by analysing the round trip time (RTT) value, conversion delay, and power consumption. The RTT value for MQTT-CoAP required 0.5 s while the CoAP-MQTT was accumulated in 0.1 s for single-packet transmission. In addition, the SDN controller and the conversion server only consumed less than 1% central processing unit (CPU) usage during the experiment. The result indicated that the proposed conversion server could handle the translation even though there was an overwhelming request from the clients. [ABSTRACT FROM AUTHOR]

Wireless sensor networks (WSN) Environment is a collection of nodes that sensing and sending data to other nodes in a large number of nodes. One of the WSN concepts is continuous or periodic data collection, then the data obtained can be further processed. From this process, it is possible to produce large data, so the process of sending and storing data becomes a high load. Data obtained from WSN nodes vary greatly, which affects on sending and storing of data. Therefore, a study is needed to analyze WSN's ability to send and store large amounts of data. Message query telemetry protocol (MQTT) is used because it could save resources on communication and MongoDB used because it does not have the concept of tables and rows, this is very suitable for variations in data generated by WSN. In this study, it can be concluded that the performance of MongoDB on high data amount is acceptable, so MongoDB is highly recommended for WSN implementation. [ABSTRACT FROM AUTHOR]

Summary: This article presents a power management system (PMS) designed for smart homes aiming to deal with the new challenges imposed by the proliferation of plug‐in electric vehicles (EVs) and their coexistence with other residential electrical appliances. The PMS is based on a hybrid wireless network architecture composed by a local hub/gateway and several Bluetooth Low Energy (BLE) and Wi‐Fi sensor/actuator devices. These wireless devices are used to transfer information inside the smart home using the Message Queuing Telemetry Transport (MQTT) protocol. Based on the proposed solution, the current consumption of the EV battery charger and other residential electrical appliances are dynamically monitored and controlled by using a configurable algorithm, ensuring that the total current consumption does not cause the tripping of the home circuit breaker. An Android client application allows the user to monitor and configure the system operation in real‐time, a developed Wi‐Fi smart plug permits to measure the RMS values of current of the connected electrical appliance and change its state of operation remotely, and an EV battery charger may be controlled in terms of operating power according to set‐points received from the Android client application. Experimental tests are used to evaluate the quality of service provided by the developed smart home platform in terms of communication delay and reliability. An experimental validation for different conditions of operation of the proposed smart home PMS concerning the power operation of the EV battery charger with the proposed control algorithm is also presented. [ABSTRACT FROM AUTHOR]

The rapid development of the Internet of Things (IoT) and the wide area of application rise the IoT concept to be the future of the internet. Indeed, IoT environment has a special nature with a lot of constraints in term of resource consumption. Moreover, the data exchanged between things and the internet is big data. In order to achieve efficiency in IoT communication, many technologies and new protocols based on these technologies have been developed. This paper aims to study the performance of Message Queuing Telemetry Transport (MQTT) by implementing this protocol on test-bed network infrastructure and analyzing the performance properties such as delay, jitter, packet loss and throughput for real time and non-real time scenarios. Finally, future research issues in MQTT protocol are suggested. [ABSTRACT FROM AUTHOR]