Internet Of Things Communication Protocols Research Articles

Future Industrial Applications: Exploring LPWAN-Driven IoT Protocols.

The Internet of Things (IoT) will bring about the next industrial revolution in Industry 4.0. The communication aspect of IoT devices is one of the most critical factors in choosing the device that is suitable for use. Thus far, the IoT physical layer communication challenges have been met with various communications protocols that provide varying strengths and weaknesses. This paper summarizes the network architectures of some of the most popular IoT wireless communications protocols. It also presents a comparative analysis of some of the critical features, including power consumption, coverage, data rate, security, cost, and quality of service (QoS). This comparative study shows that low-power wide area network (LPWAN)-based IoT protocols (LoRa, Sigfox, NB-IoT, LTE-M) are more suitable for future industrial applications because of their energy efficiency, high coverage, and cost efficiency. In addition, the study also presents an Industrial Internet of Things (IIoT) application perspective on the suitability of LPWAN protocols in a particular scenario and addresses some open issues that need to be researched. Thus, this study can assist in deciding the most suitable IoT communication protocol for an industrial and production field.

Incorporating the Internet of Things (IoT) Learning Module into the Smart Building Course

The utilization of Internet of Things (IoT) devices is increasing very rapidly, creating a demand for skilled professionals who can navigate the complexities of this technology. It is a crucial educational challenge to prepare undergraduates to become contributors in this emerging field. The curriculum needs to be updated to offer students both theoretical learning and practical application so they can benefit from it. This paper introduces a comprehensive IoT learning module to the final-year students of civil engineering in an elective course, Smart Building. The proposed learning module includes an introduction to IoT concepts and applications, IoT devices, communication protocols, cloud platforms, user interfaces, and IoT risk management and security, all of which can be easily integrated into existing courses. Results from the module are presented using direct and indirect assessments, including assignments, hands-on practical, examinations, and surveys. These assessments are designed to evaluate the students’ understanding and the challenges they encountered in their IoT learning process. The findings indicate that a significant majority, surpassing 90% of the students, have demonstrated understanding of a minimum of three essential components of the fundamental IoT architecture, despite their limited background knowledge at the beginning of the course. Additionally, this learning module can serve as a valuable resource for other educators who intend to deliver IoT-related courses.

Service for communication of devices with Internet access: analysis of technologies and method of creation

The subject of study in this article is technologies and services of communication of elements of smart home, as well as the models, methods, and tools for prototyping of interaction of devices for Internet of Things (IoT). The goal is to simplify the process of creation a service for the programmable by an end user device with the ability to communicate over Internet and to simplify the process of choosing the components for such devices. Task: to perform the analysis of IoT systems requirements and possible issues during the process of creation; to perform the analysis of requirements of safety and cybersecurity for IoT systems; to perform the research and classification of components of IoT systems; to perform the research of communication process between elements of IoT system; to analyze IoT communication protocols; to perform the analysis of services for IoT communication; propose the models of communication of IoT nodes; propose technique for creation of service; and provide practical example of implementation of the research results. According to the tasks, the following results were obtained. The analysis of possible problems and requirements for prototyping elements of smart home systems with Internet access is performed. The analysis of the existing architectures layers of IoT systems is performed. Models of Edge and Fog for IoT system are considered. Analysis of cybersecurity considerations for the devices communication is performed. Five types of components for smart home systems were classified. The process of communication of smart home elements with service at the model level is described. Existing communication protocols for the communication of devices over Internet are analyzed. Commercial and open source communication services for different types of devices are analyzed. Models of IoT node interaction are proposed. Technique of creation of a service for communication of devices and example of use are proposed. Conclusions. The main contribution of this research is the proposed method of creation of own service for communication over Internet for devices implemented on the basis of widely used microcontrollers. Based on the proposed classification of IoT hardware components, it is possible to simplify the decision-making process of selection based on the parameters of price, required efforts from the end customer for installation, and expandability in terms of the possibility of integration of the solution with wider systems. The performed analysis allows to conclude that from existing services ThingSpeak is interesting for use with the simplest chips, and Home Assistant is the preferable solution for home automation.

Securing Internet of Things (IoT) Ecosystems: A Quantum Cryptography Approach

In order to strengthen the stability of IoT ecosystems, this study explores the interface between Internet of Things (IoT) security and quantum cryptography. Our study goals included assessing the applicability of quantum key distribution, correcting flaws, and investigating the influence of environmental variables on security. We reveal fascinating insights through experimental research that alter IoT security paradigms. A comparison of the typical key setup durations and data transmission rates across various IoT devices and communication protocols shows how effective quantum cryptography is in speeding up key distribution. This effectiveness fits the changing environment of secure communication technologies. Our vulnerability evaluation also shows that quantum key distribution is a potent defense against weaknesses like man-in-the-middle and replay assaults. It is made clear how contextual factors and security interact, emphasizing the importance of adaptable security measures in line with environmental circumstances. We present a comprehensive methodology that balances security with deployment circumstances by merging this contextual sensitivity with quantum cryptography concepts. Our research points to prospective directions for joint investigation between quantum physicists and IoT developers to close the gap between theoretical promise and actual use. Comprehensive insights will be obtained by scaling the use of quantum cryptography to larger IoT networks and other circumstances, but caution is needed to survive the upcoming quantum computing era. The study's conclusion ignites a paradigm change and pushes the quantum revolution into IoT security. Our research promotes more investigation, innovation, and application as we stand on the brink of a new era, protecting IoT ecosystems in a quantum-secure embrace.

Internet of Things: A Comprehensive Overview on Protocols, Architectures, Technologies, Simulation Tools, and Future Directions

The Internet of Things (IoT) is a global network of interconnected computing, sensing, and networking devices that can exchange data and information via various network protocols. It can connect numerous smart devices thanks to recent advances in wired, wireless, and hybrid technologies. Lightweight IoT protocols can compensate for IoT devices with restricted hardware characteristics in terms of storage, Central Processing Unit (CPU), energy, etc. Hence, it is critical to identify the optimal communication protocol for system architects. This necessitates an evaluation of next-generation networks with improved characteristics for connectivity. This paper highlights significant wireless and wired IoT technologies and their applications, offering a new categorization for conventional IoT network protocols. It provides an in-depth analysis of IoT communication protocols with detailed technical information about their stacks, limitations, and applications. The study further compares industrial IoT-compliant devices and software simulation tools. Finally, the study provides a summary of the current challenges, along with a broad overview of the future directions to tackle the challenges, in the next IoT generation. This study aims to provide a comprehensive primer on IoT concepts, protocols, and future insights that academics and professionals can use in various contexts.

Detecting while accessing: A semi-supervised learning-based approach for malicious traffic detection in Internet of Things

In the upcoming large-scale Internet of Things (IoT), it is increasingly challenging to defend against malicious traffic, due to the heterogeneity of IoT devices and the diversity of IoT communication protocols. In this paper, we propose a semi-supervised learning-based approach to detect malicious traffic at the access side. It overcomes the resource-bottleneck problem of traditional malicious traffic defenders which are deployed at the victim side, and also is free of labeled traffic data in model training. Specifically, we design a coarse-grained behavior model of IoT devices by self-supervised learning with unlabeled traffic data. Then, we fine-tune this model to improve its accuracy in malicious traffic detection by adopting a transfer learning method using a small amount of labeled data. Experimental results show that our method can achieve the accuracy of 99.52% and the F1-score of 99.52% with only 1% of the labeled training data based on the CICDDoS2019 dataset. Moreover, our method outperforms the state-of-the-art supervised learning-based methods in terms of accuracy, precision, recall and F1-score with 1% of the training data.

Transformer-Based Device-Type Identification in Heterogeneous IoT Traffic

Due to the heterogeneity of Internet of Things (IoT) devices and the diversity of IoT communication protocols, it is challenging to model the communication behaviors of IoT devices to facilitate attack defense. Considering the complex correlation between the IoT device types and the patterns of their communication behaviors, one possible solution is to cluster IoT devices into different types based on the characteristics of their communication behaviors and deal with each type, respectively. However, IoT traffic includes a significant proportion of abnormal traffic, such as attack traffic sourcing from compromised devices, which cannot reflect the behavioral characteristics of the source device. In this article, we propose a Transformer-based IoT device-type identification method to address the above challenges. Specifically, our approach consists of three main components. First, we classify the traffic data from IoT devices into normal and abnormal types by a Transformer-based traffic diagnosis model. Next, another Transformer-based model is adopted on the normal traffic to identify the IoT device type. Finally, considering the immutability of IoT device types, a results-ensemble algorithm is designed to improve the accuracy of IoT device-type identification. Experimental results verify the effectiveness of our method, which brings a noticeable improvement in terms of both accuracy and macro <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$F1$ </tex-math></inline-formula> -score compared to other methods. Moreover, by applying the results-ensemble algorithm in the test phase, we can achieve 100% accuracy under certain conditions.

Automatic Vulnerability Detection in Tizen Applications with Dynamic Symbolic Execution

Security of Internet-of-Things (IoT) systems is important due to their widespread usage in everyday life. Much research has been performed on analyzing the security of IoT communication protocols and operating systems. However, few studies have focused on analyzing the security of IoT applications and automatic detection of vulnerabilities in them. In these studies, the code of IoT applications and operating systems are analyzed statically to detect vulnerabilities. To the best of our knowledge, there is no dynamic analysis solution suggested for vulnerability detection in such applications, although this method is more accurate than static analysis. In fact, IoT applications are executed in special-purpose hardware, which makes their dynamic analysis more difficult than ordinary applications. In this paper, we propose a technical solution that combines static and dynamic analysis methods to automatically detect vulnerability in applications of Tizen IoT operating system. We consider Native and Web Tizen applications and present an automatic vulnerability detection method for each type of application. Our focus is on detecting buffer overflow and XSS vulnerability classes in Native and Web applications, respectively. We have evaluated the effectiveness of our method using a group of native and web test programs. The results of our experiments show that our solution is able to detect the vulnerability in these programs effectively.

Centralized Control Method for Voltage Coordination Challenges With OLTC and D-STATCOM in Smart Distribution Networks Based IoT Communication Protocol

This paper proposes a coordination method for the voltage control devices based on optimal settings of the D-STATCOMs, on the load tap changer (OLTC) transformer and the distributed generations (DGs)-based renewable energy resources (RERs). The central controller is introduced to handle the active smart distribution network (SDN) problems to maintain the voltage profile within its permissible limits, minimize power losses in different operating conditions, and minimize the energy wastage from the distributed renewable energy resources. These problems are formulated as a multi-objective optimization problem. With increasing load demand and RERs in the distribution system, voltage coordination threatens real-time efficiency. In this research work, central controller-based Gorilla Troops optimization (GTO) algorithm is proposed to detect the optimum solutions for the voltage coordination problem. The load demand uncertainty and the stochastic nature of power generated from RERs (PV panels and wind turbines) are considered in the voltage coordination problem due to their significant effects on the operation and planning of the SDN. The proposed SDN has been represented based on the Internet of Things (IoT) communication protocol. It enhances the data and information transfer between the system-connected agents. A practical test system, NDEDC-24 bus radial distribution network from the North Delta Electrical Distribution Company and IEEE-33 node system are used to test and evaluate the proposed method. The results are compared with other well-known evolutionary methods. The proposed method obtains more accurate results than the other methods.

Algorithms for composing communication protocols of wireless sensor networks with random access

The work is devoted to solving the problem of applying information technology methods and tools to monitoring environmental parameters based on the Internet of Things concept, taking into account the uncertainty of information sources and the possibility of critical situations. The principles of construction, technological solutions and directions of development of environmental monitoring systems are analyzed. The advantages and disadvantages of the known approaches are revealed and the expediency of constructing mathematical models, methods and algorithms for compiling communication protocols of WSN wireless sensor networks with random access and corresponding information technologies for monitoring environmental parameters to ensure high performance, quality and survivability of their functioning is proved. Stochastic models of the functioning of wireless sensor networks have been improved, which made it possible to estimate the probability of signal collisions and design Internet of Things communication protocols more efficiently.

THE USE OF INTERNET-BASED TECHNOLOGIES IN DIETARY AND PHYSICAL ACTIVITY INTERVENTION FOR PATIENTS WITH HYPERTENSION: A SYSTEMATIC REVIEW

The Internet of Things (IoT) is widely used in Internet-based technology (IBT) interventions for hypertension management. However, little is known about the impact of IBT and how the IoT is used to manage hypertension. This article analysed the types of IBT, the features of IoT and the impact of IBT. This review included 14 articles selected from the following databases: Scopus, Web of Science, PubMed, ScienceDirect and Google Scholar. Randomised controlled trials (RCT) and quasi-experimental studies published from 2014 to 2021 in English focused on managing dietary intake and physical activity (PA) via IBT for hypertensive adults were included. The IoT features, Mobile IoT and Wi-Fi communication protocols were covered by three articles while six digital platforms (smartphone applications, email, WeChat, url, web page and online multimedia) were utilised for the non-pharmacological management. The current review identified the important features of IoT and how implementing IBT in hypertension management can effectively improve blood pressure and bring about behavioural and psychological changes. Finally, this study highlighted only limited IoT systems that had been integrated into IBT, thus, warranting the need for further studies in the future.

System Identification at the Extreme Edge for Network Load Reduction in Vibration-Based Monitoring

Mechanical complexity, wide dimensions, and big data volume may hamper the implementation of Internet of Things (IoT)-enabled structural health monitoring (SHM) systems. In particular, one of the most important challenges is the reduction of the data payload to be transmitted over the monitoring network. Addressing the problem in the context of vibration-based SHM, this work explores system identification (SysId) as an innovative strategy for data compression at the extreme edge. Indeed, SysId is a signal processing technique aiming at finding a very reduced (i.e., less then one tenth of the total signal length) set of meaningful parameters, which can provide an alternative, but yet completely equivalent, frequency characterization of the structure. In the proposed approach, an embedded system-oriented adaptation of the sequential tall-skinny QR decomposition (eS-TSQR) from the dense linear algebra domain has been exploited to tackle both the memory and computational complexity of the involved algorithms. This yielded to the embodiment of input–output and output-only SysId models into a resource constrained device (i.e., an STM32L5 microcontoller unit), targeted on low-power and low-cost SHM applications, proving high effectiveness for the structural assessment of civil and industrial plants. Besides, a cost-benefit analysis is also presented, in which the energy saving brought by SysId running in a sensor-near manner is comprehensively measured against the power consumption due to data transmission, as implied by state-of-the-art communication protocols for IoT. Results demonstrate that SysId is <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$1.19\times $ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2.78\times $ </tex-math></inline-formula> less energy demanding (with a payload reduction of <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$9\times $ </tex-math></inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$45\times $ </tex-math></inline-formula> ) w.r.t. compressed sensing-driven and compression-free solutions, respectively.

System Design and Simulation for Square Dance Movement Monitoring Based on Machine Learning.

Since the reform and opening, China's economy has grown rapidly, and people's living standards have improved significantly. As one of the most effective ways to implement national fitness, square dance has gradually become the main lifestyle of urban communities, an important part of China's sports construction, and an important indicator to reflect the fitness of the masses and the construction of a well-off society in an all-round way. On the other hand, with the rapid development of internet of things technology, many people can use intelligent bracelets based on machine learning technology to realize motion detection. This technology is also applicable in square dance, which is of great significance to exercise and protect health. This paper first reviews the research status of the internet of things communication protocol and cloud platform, then introduces and analyzes the MQTT communication protocol and Netty high-performance network framework, and studies the integration technology of the internet of things and machine learning. Then, according to the characteristics of the internet of things, a scheme to realize data preprocessing is proposed. The value to be completed is calculated based on the correlation of other attributes corresponding to the k-nearest neighbor model (KNN) and the regression model. Finally, the machine learning algorithm is used to train the results of the three models to obtain the final filling value. The whole scheme design allows the machine learning algorithm to obtain relatively high-quality data in the internal environment. This paper designs a sports monitoring data system for square dance by combining machine learning and internet of things technology, so as to promote national fitness.

Secure Communication Protocol for Arduino-based IoT Using Lightweight Cryptography

We witness massive implementations of the Internet of Things (IoT) in smart homes, smart buildings, smart vehicles, smart wearables as well as Industry 4.0 initiatives. Along with the massive adoption, IoT security has become more important and crucial in this case. Arduino, as IoT hardware platform, also requires enhancements on its security to ensure that data it transmits and receives is secured and has not been tampered in any way. Transmitting of IoT data and telecommand in plaintext is not secure. Securing transmission using traditional block cipher is computationally intensive for embedded-systems with low memory and computing power like Arduino. This research proposes a novel lightweight security communication protocol that is lightweight enough to run on the Arduino platform. The proposed protocol shall be utilizing a lightweight key agreement scheme, the SPECK lightweight block cipher, and BLAKE2s hash function. This protocol is designed to support telemetry and telecommand by using publisher-subscriber, which also is aimed to be extensible but straightforward for future enhancements. This research shows that a secure IoT communication protocol can be designed and implemented on Arduino devices and another IoT platform running Arduino core such as the ESP32. The performance evaluation of this protocol in Arduino Mega shows that the INIT phase's average execution time is 26.83 milliseconds. The key agreement is 13.50 milliseconds, and the encryption-decryption of telemetry and telecommand messages requires 25 milliseconds execution time. The protocol performance evaluation in ESP32 has an average execution time for INIT phase 44.63 milliseconds. The key agreement phase, 13.90 milliseconds, and the encryption and decryption of telemetry and telecommand messages requires an execution time of 17.10 milliseconds.

QoS‐aware IoT networks and protocols: A comprehensive survey

SummaryThe vast number of smart cloud applications that communicate with the “things” over a variety of physical networks and communication protocols contribute to the rise of complexity in Internet of Things (IoT) systems. The diversity of end‐user requirements related to the volume of generated data, its variety, and the velocity of its transmission makes quality of service (QoS) provisioning even more crucial and challenging in IoT. This paper provides a comprehensive and up‐to‐date survey of QoS support in IoT networks and communication protocols. An analysis of the QoS‐aware IoT architectures, layer‐dependent QoS metrics, and network resource optimization methods utilized in IoT systems are given. The limitations of the current state‐of‐the‐art studies for efficient delivery of QoS metrics are discussed. The paper concludes with future research directions on end‐to‐end QoS provisioning in IoT.

A survey on communication protocols and performance evaluations for Internet of Things

The Internet of Things (IoT) is a large-scale network of devices capable of sensing, data processing, and communicating with each other through different communication protocols. In today's technology ecosystem, IoT interacts with many application areas such as smart city, smart building, security, traffic, remote monitoring, health, energy, disaster, agriculture, industry. The IoT network in these scenarios comprises tiny devices, gateways, and cloud platforms. An IoT network is able to keep these fundamental components in transmission under many conditions with lightweight communication protocols taking into account the limited hardware features (memory, processor, energy, etc.) of tiny devices. These lightweight communication protocols affect the network traffic, reliability, bandwidth, and energy consumption of the IoT application. Therefore, determining the most proper communication protocol for application developers emerges as an important engineering problem. This paper presents a straightforward overview of the lightweight communication protocols, technological advancements in application layer for the IoT ecosystem. The survey then analyzes various recent lightweight communication protocols and reviews their strengths and limitations. In addition, the paper explains the experimental comparison of Constrained Applications Protocol (CoAP), Message Queuing Telemetry (MQTT), and WebSocket protocols, more convenient for tiny IoT devices. Finally, we discuss future research directions of communication protocols for IoT.

The Smarter Safer Homes Solution to Support Older People Living in Their Own Homes Through Enhanced Care Models: Protocol for a Stratified Randomized Controlled Trial.

BackgroundAn aging population, accompanied by the prevalence of age-related diseases, presents a significant burden to health systems. This is exacerbated by an increasing shortage of aged care staff due to the existing workforce entering their retirement and fewer young people being attracted to work in aged care. In line with consumer preferences and potential cost-efficiencies, government and aged care providers are increasingly seeking options to move care and support to the community or home as opposed to residential care facilities. However, compared to residential care, home environments may provide limited opportunity for monitoring patients’ progression/decline in functioning and therefore limited opportunity to provide timely intervention. To address this, the Smarter Safer Homes (SSH) platform was designed to enable self-monitoring and/or management, and to provide aged care providers with support to deliver their services. The platform uses open Internet of Things communication protocols to easily incorporate commercially available sensors into the system.ObjectiveOur research aims to detail the benefits of utilizing the SSH platform as a service in its own right as well as a complementary service to more traditional/historical service offerings in aged care. This work is anticipated to validate the capacity and benefits of the SSH platform to enable older people to self-manage and aged care service providers to support their clients to live functionally and independently in their own homes for as long as possible.MethodsThis study was designed as a single-blinded, stratified, 12-month randomized controlled trial with participants recruited from three aged care providers in Queensland, Australia. The study aimed to recruit 200 people, including 145 people from metropolitan areas and 55 from regional areas. Participants were randomized to the intervention group (having the SSH platform installed in their homes to assist age care service providers in monitoring and providing timely support) and the control group (receiving their usual aged care services from providers). Data on community care, health and social-related quality of life, health service utilization, caregiver burden, and user experience of both groups were collected at the start, middle (6 months), and end of the trial (12 months).ResultsThe trial recruited its first participant in April 2019 and data collection of the last participant was completed in November 2020. The trial eventually recruited 195 participants, with 98 participants allocated to the intervention group and 97 participants allocated to the control group. The study also received participants’ health service data from government data resources in June 2021.ConclusionsA crisis is looming to support the aging population. Digital solutions such as the SSH platform have the potential to address this crisis and support aged care in the home and community. The outcomes of this study could improve and support the delivery of aged care services and provide better quality of life to older Australians in various geographical locations.Trial RegistrationAustralian New Zealand Clinical Trials Registry ACTRN12618000829213; https://tinyurl.com/2n6a75emInternational Registered Report Identifier (IRRID)DERR1-10.2196/31970

Lightweight Payload Encryption-Based Authentication Scheme for Advanced Metering Infrastructure Sensor Networks.

The Internet of Things (IoT) connects billions of sensors to share and collect data at any time and place. The Advanced Metering Infrastructure (AMI) is one of the most important IoT applications. IoT supports AMI to collect data from smart sensors, analyse and measure abnormalities in the energy consumption pattern of sensors. However, two-way communication in distributed sensors is sensitive and tends towards security and privacy issues. Before deploying distributed sensors, data confidentiality and privacy and message authentication for sensor devices and control messages are the major security requirements. Several authentications and encryption protocols have been developed to provide confidentiality and integrity. However, many sensors in distributed systems, resource constraint smart sensors, and adaptability of IoT communication protocols in sensors necessitate designing an efficient and lightweight security authentication scheme. This paper proposes a Payload Encryption-based Optimisation Scheme for lightweight authentication (PEOS) on distributed sensors. The PEOS integrates and optimises important features of Datagram Transport Layer Security (DTLS) in Constrained Application Protocol (CoAP) architecture instead of implementing the DTLS in a separate channel. The proposed work designs a payload encryption scheme and an Optimised Advanced Encryption Standard (OP-AES). The PEOS modifies the DTLS handshaking and retransmission processes in PEOS using payload encryption and NACK messages, respectively. It also removes the duplicate features of the protocol version and sequence number without impacting the performance of CoAP. Moreover, the PEOS attempts to improve the CoAP over distributed sensors in the aspect of optimised AES operations, such as parallel execution of S-boxes in SubBytes and delayed Mixcolumns. The efficiency of PEOS authentication is evaluated on Conitki OS using the Cooja simulator for lightweight security and authentication. The proposed scheme attains better throughput while minimising the message size overhead by 9% and 23% than the existing payload-based mutual authentication PbMA and basic DTLS/CoAP scheme in random network topologies with less than 50 nodes.

Research on Data Acquisition Technology of Distribution Automation Based on Internet of Things Communication Protocol

With the gradual application of the Internet of Things technology in the field of distribution automation, distribution terminals gradually adopt the Internet of Things protocol to communicate with the master station system of distribution automation. while the master station system of distribution automation supports the access of the traditional power dedicated protocol terminal, it faces how to solve the problem which how to access the distribution terminal of the network communication protocol. This paper proposes the MQTT protocol data acquisition architecture based on the existing master station system of distribution automation system. Through the research on the transmission characteristics of power distribution service data and MQTT protocol, the message structure of the MQTT protocol carrying power service data and the source maintenance process of the equipment model are designed., It realizes the direct collection of the terminal data of the distribution Internet of Things in an object-oriented way, gives full play to the value of the existing distribution master station, reduces investment costs, and saves system maintenance workload.

A Review on existing IoT Architecture and Communication Protocols used in Healthcare Monitoring System

Nowadays, due to modernization or advancement in the Internet of Things (IoT) especially in the Healthcare area, we want to take care of our elders with some monitoring equipment, and the Internet of Things can play a significant role in it. The motivation of writing this paper is to collect the information of various existing Internet of Things Architecture and Communication Techniques used in Healthcare Monitoring System to observe that how efficiently, different researchers have used it. So we have studied different real-time health monitoring system based on diseases which are common in elderly people like diabetes, blood pressure, heart disease, sleep apnea, and cancer, etc. In this real-time health monitoring system, researchers introduced many new measures, communication techniques like ZigBee, Long-Range Wide Area Network (LoRawan), Radio Frequency Identification (RFID). Apart from this, it was also observed that remote monitoring system in Healthcare is incomplete without data processing and early prediction in such diseases. Though, Machine learning provides efficient techniques to extract knowledge from diagnostic medical datasets collected from the patients. That is why we highlighted the current role of various Machine Learning algorithms like Support Vector Machine, K-Nearest Neighbor, Random Forest, etc., for processing of Healthcare data and also helpful to predict the output more precisely.