Network Of Interconnected Devices Research Articles

IoT Approach for Ensuring Safety in smart Cities for Energy Saving

The security of city dwellers is of the utmost importance due to the increasing number of smart cities and the speed with which they are being developed. As a whole, smart city safety can be improved through the use of the Internet of Things (IoT), which is the focus of this article. Several safety concerns, such as public safety, emergency management, and disaster preparedness, can be monitored and addressed with the help of the Internet of Things (IoT) framework's network of interconnected devices, sensors, and data analytics. In order to improve situational awareness, reaction times, and overall safety results, this research dives into important Internet of Things (IoT) applications such smart sensors, real-time analytics, and surveillance systems. In addition to looking at potential energy savings, the study analyses the pros and cons of using an Internet of Things (IoT) safety infrastructure in smart cities.

Navigating the Landscape of IoT, Distributed Cloud Computing: A Comprehensive Review

This comprehensive academic exploration delves into the revolutionary convergence of the Internet of Things (IoT) with distributed cloud computing, redefining the realms of data processing, storage, and communication. The paper critically analyzes scholarly work from reputable journals, providing profound insights into this integration's multifaceted applications and underlying technological frameworks. The relevance of IoT, a network of interconnected devices and sensors, is emphasized through its significant impact on diverse sectors, including healthcare, education, agriculture, and smart cities. This impact is magnified by its extensive data collection, processing, and analysis capabilities, enabled through cloud computing platforms. The objective of the paper is to methodically compare and contrast contemporary scholarly contributions, shedding light on the diverse applications and technological infrastructures of IoT in conjunction with distributed cloud computing. This endeavor encompasses an examination of IoT-based cloud infrastructure, detailed analysis of specific needs, implementations, and applications of IoT-based cloud computing, and a review of various IoT cloud platforms. The paper also highlights the benefits of integrating IoT with cloud computing, elucidating significant advantages and potential future directions of this technology. Through this scholarly inquiry, the paper aims to offer an in-depth perspective on the state-of-the-art developments in IoT and distributed cloud computing. It underscores their significance and potential in shaping the future of digital technology and its applications across various domains.

HealthNet: IoT-based Healthcare Monitoring and Management System

Abstract: The Internet of Things (IoT) is a network of interconnected devices that can collect, store, analyze and transmit data over the Internet. IoT has the potential to revolutionize the healthcare industry by enabling remote patient care, telemedicine, electronic medical records, medication management, imaging and monitoring. The Internet of Things can also improve patient safety, reduce healthcare costs, increase healthcare accessibility, and increase efficiency. However, IoT in healthcare still faces challenges such as security, privacy, wearability, and design. This article reviews the latest research on IoT in healthcare, focusing on the technology, applications, benefits, and challenges of IoT in healthcare

Behavioral fingerprinting to detect ransomware in resource-constrained devices

The Internet of Things (IoT), a network of interconnected devices, has grown and gained traction over the last few years. This paradigm can impact our lives while also providing significant economic benefits. However, although resource-constrained IoT devices offer numerous advantages, they are also vulnerable to cyberattacks. As a result, ransomware severely threatens IoT devices managing sensitive and relevant information. Solutions based on Machine and Deep Learning (ML/DL) that consider behavioral data have been identified as promising. However, most detection solutions have been developed for Windows-based systems, which generally have more resources than IoT devices. As a result, these solutions are not suitable for resource-constrained components. In addition, no solution compares the pros and cons of different behavioral dimensions of resource-constrained devices. Thus, this work presents a framework that combines three different behavioral sources with supervised and unsupervised ML/DL algorithms to detect and classify heterogeneous ransomware impacting resource-constrained spectrum sensors. A pool of experiments has demonstrated the suitability of the proposed solution and compared its performance with a rule-based system. In conclusion, the usage of resources combined with local outlier factor and decision tree are the most promising combinations to detect anomalies and classify ransomware while consuming CPU, RAM, and time of devices in a reduced manner.

Machine Learning-Based DoS Amplification Attack Detection against Constrained Application Protocol

This paper discusses the Internet of Things (IoT) and the security challenges associated with it. IoT is a network of interconnected devices that share information. However, the low power and resources of IoT devices make them vulnerable to attacks. Using heavy protocols like HTTP for IoT devices can prove costly and using popular lightweight protocols like CoAP can invite attacks such as DoS (Denial-of-Service). While security models such as DTLS and LSPWSN can secure IoT against such attacks, they also have limitations. To overcome this problem, this paper proposes a machine learning model that detects DoS amplification attacks against CoAP with 99% accuracy. To the best of our knowledge, this research is the first to use the multi-classification process to detect and classify the different types of the DoS amplification techniques that attack CoAP client use against victim CoAP clients.

An enhanced opportunistic rank-based parent node selection for sustainable & smart IoT networks

The Internet of Things (IoT) is a network of interconnected devices that includes low-end devices (sensors) and high-end devices (servers). The routing protocol used the Low-Power and Lossy Networks (RPL) protocol, which was designed to collect data in Low-Power and Lossy Networks (LLN) efficiently and reliably. The RPL rank property specifies how sensor nodes are placed in Destination Oriented Directed Acyclic Graphs (DODAG) based on an Objective Function (OF). The OF includes information such as the Expected Transmission Count (ETX) and packet delivery rate. The rank property aids in routing path optimization, reducing control overhead, and maintaining a loop-free topology by using rank-based data path validation. However, it causes many issues, such as optimal parent selection, next-hop node selection, and network instability. We proposed an Enhanced Opportunistic Rank-based Parent Node Selection for Sustainable and Smart IoT Networks to address these issues. The optimal parent node is determined by forecasting the expected energy of each node using Received Signal Strength (RSS) and an enhanced reinforcement learning algorithm. The proposed method addresses the issue of selecting the next-hop neighbor node and improves routing stability. Furthermore, when a large number of new nodes try to join the sustainable IoT-based smart cities, the proposed technique provides optimal load balance.

Monitoring of an Electromechanical Prototype Material for Environmental Parameters Using IoT

The Internet of Things (IoT) is a phenomenon where everything is connected to everything, where the development of sensors and microprocessors helped in the rise of embedded technologies, such as Wi-Fi and Bluetooth, and the evolution of bandwidth available on the Internet. This phenomenon will continue unabated due to sensor technology, programmable chips, and embedded technologies. In recent years, the Internet of Things (IoT) has become one of the most prominent technology niches. IoT is the network of interconnected devices or “things” that exchange information or send data with each other over the Internet. The article describes a computer prototype for monitoring and controlling the environmental parameters of a communication equipment room. A technological tool, such as the one obtained, can be implemented in many applications, such as weather stations, food chains, smart home systems, measuring the heart rate of humans, and fruit dehydrators. The article’s research was focused on an IoT electronic device and a web platform. A major feature of this electronic device is that its Internet connectivity is achieved using the TCP/IP protocol, an integrated feature of the Shield Ethernet board stacked on top of the Arduino mega board.

Revolutionizing Supply Chain Management: The Impact of IoT on Efficiency and Transparency

The digital age has brought us numerous advancements in technology, and the Internet of Things (IoT) is one of the most transformative. IoT, a network of interconnected devices and sensors that collect and exchange data, has the potential to significantly improve supply chain management (SCM). This article will explore some great IoT innovations and examine how they enhance SCM operations in terms of efficiency, visibility, and transparency.

IoT Based Emergency Button for Women Safety

Abstract: Fundamental to IoT is the instant collaboration that happens between these smart devices. The beauty behind having a network of interconnected devices is that they can all work together to provide real solutions that are much greater than the sum of their parts. IOT based products are always connected and constantly communicating with each other. They regularly exchange information using wired and wireless networks, which helps make our lives easier and safer. When IoT based smart home security systems are used to safeguard our home or possessions, it’s akin to having our favorite reliable friend dutifully watching over our home or pets in our absence. Except it’s actually way better than that, because unlike our well-meaning friend or neighbor, smart home security systems are always present and are ready to instantly alert us of any signs of danger. Smart products, like Nest Lab’s smoke and carbon monoxide alarm, sounds an alert when it detects high levels of CO, and then warns us of the location of the danger. It’s no wonder that Google acquired Nest Labs for a whopping $3.2 billion! Other companies like Canary offer connected smart home security systems that are now a part of a growing trend: using IoT technology to create safety solutions to protect what’s most valuable to us.

A Literature Survey on Smart Agriculture Monitoring and Control System Using IOT

Abstract: India is agriculture sector, on either side, is losing ground every day, affecting the ecosystem's output capacity. In order to restore vitality and put agriculture back on a path of higher growth, there is a growing need to resolve the issue. A large-scale agricultural system necessitates a great deal of upkeep, knowledge, and oversight. The IoT is a network of interconnected devices that can transmit and receive data over the internet and carry out tasks without human involvement. Agriculture provides a wealth of data analysis parameters, resulting in increased crop yields. The use of IoT devices in smart farming aids in the modernization of information and communication. For better crop growth moisture, mineral, light and other factors can be assumed. This research looks into a few of these characteristics for data analysis with the goal of assisting users in making better agricultural decisions using IoT. The technique is intended to help farmers increase their agricultural output. Keywords: Soil, Rain, Sensors, IoT, Smart Irrigation

IOT BASED MOLECULAR MARKERS FOR DISEASE RESISTANCE STUDIES IN RICE - STRATEGY AND CHALLENGES

Rice production is constrained by diseases of fungal, bacterial and viral origin. The Internet of Things (IoT) – network of interconnected devices - is an application for disease related uses, collection of data, processing for testing and monitoring. This review article aims about how IoT can track and allows disease resistance studies in in Oryza species. Among them Xanthomonas oryzae, Magnaporthe grisea, RYMV (Rice yellow mottle virus), and brown planthopper causes the high yield losses. Disease resistance genes are identified and they are screened by the SSR (simple sequence repeats), RAPD (Randomly Amplified Polymorphic DNA) and RFLP (restriction fragment length polymorphisms) analysis.

Generic framework for industrial 4.0 applications based on internet of things

The Internet of Things (IoTs) is a network of interconnected devices, transportations, home appliances, and other devices. They are functionally embedded in electronics, software, sensors, actuators, and connectivity that allows them to connect and exchange information. On the basis of the IoT concept, implementations are gradually being proposed in a range of areas, ranging from smart house, smart office and smart agriculture. In this research paper, a generic framework for smart monitoring applications based on the IoTs network is proposed. In this framework, low-powered sensor nodes are based on the micro:bit platform, providing a multiple footprints for different sensor connections. The wireless capability on micro:bit provides a complete solution to deploy the system in such places that wire is impractical to draw. The data is wirelessly gathered by a basestation node that is powered by Android Things operating system provided by Google. This operating system is based on the Android platform for smart devices and Internet of Things products. The approach to this framework indicates a low cost and minimum setup and especially amenable for applications control. To support many applications with minimum modifications, the framework is designed for easy expansion by supporting popular serial connection ports, including the Universal Asynchronous Receiver/Transmitter and Serial Peripheral Interface. With these connections, on one line data bus, several sensors can be added to match the different application requirements. In this paper, our platform is validated for an automatic water monitoring in aquaculture based on the temperature, pH and dissolved oxygen sensory data. Through our framework, the data is uploaded to a cloud for remote monitoring and providing alarms for users whenever the data is out of a predefined safe domain.

A smart predictive framework for system-level stormwater management optimization

This study presents a global real-time control (RTC) approach for sustainable and adaptive management of stormwater. A network of inter-connected devices are assumed to dynamically generate the required set-points for the system actuators at the remote control center where global optimization algorithms calculate real-time operational decision-making target values. These target values activate the local controllers to manipulate the spatially distributed detention basin's outlets enabling a smart catchment scale optimal control. A real world watershed with four outlets to a nearby watercourse is chosen to test the applicability and efficiency of the proposed dynamic control approach, based on model simulation results. Results show that the proposed autonomous control approach has the ability to enhance the global performance of the stormwater management system in terms of quality and quantity to balance the network flow dynamics and environmental demands, while reducing the potential for erosion of receiving water bodies. Climate change is specifically discussed as a challenge for the designed control framework. Although, the performance criteria are shown to be affected by the increased rainfall intensities compared to actual rainfall scenarios, the proposed methodology still improves the peak flow reduction and detention time of water, at global scale, up to 54% and 14 h respectively under climate change conditions.

Influence of the Internet of Things’ application on construction project performance

Internet of Things (IoT) is the network of interconnected devices that are embedded with network connectivity, sensors, software that enable them to amass and exchange data making them responsive. The study is aimed at examining the effects of the IoT on construction project performance with the view of increasing productivity and efficiency. Quantitative research method was adopted and questionnaires were structured on a five-point Likert scale to elicit the opinion of respondents. Descriptive and Inferential analysis were used in analyzing the retrieved data. The most important effects of IoT are security and privacy, collecting previous data, safety comfort and efficiency. Factor analysis was used to group the various impacts of IoT into six. The results showed that there were nine variables with a significant difference while the others ten are not. It was concluded that the IoT adoption has a high influence on the security, privacy, safety, productivity and performance of construction workers. It is recommended that variables with least influenced areas can be developed by improving the skills of professionals. Government is also encouraged to adopt the principles of IoT not only in construction but other sectors to improve the economy of the nation.

Automatic Railway Gate Controlling and Smart System of Railway Gate Crossing using IoT

The main objective of this paper to propose the smart system of controlling the railway gate automatically to avoid the accident while crossing the railway gate as well as smart way of railway gate crossing using the mobile application. In this system we are using the Internet of Thing (IoT). IoT is a network of interconnected devices which are connected with sensors. For IoT device can communicate with no human inter rup ton. By implementing these, it will provide control of railway gate to the device which operates the railway gate. It reduces the time, gatekeeper carelessness for operating the gate close and open than the gatekeeper. So this system is useful for reduction of the accident at level crossing. In addition to this, one more additional feature is implemented for the driver’s convenience who can use for the level crossing . Here, driver needs to install the mobile application in their mobile by which they can check the railway gate is open or close . The Ultrasonic sensor detect the train is coming or not and with help of NodeMCU send to the Google Firebase and Firebase will send the same information to NodeMCU which is located at level crossing and close the gate with the help of Servo Motor, and when the train departure from the another side Ultrasonic Sensor it will again send data to Google Firebase and Firebase again give command to NodeMCU to open the gate which is located at level crossing. This is cost effective, real time and time saving automatic system.

Data-Driven Modelling of Smart Building Ventilation Subsystem

Considering the advances in building monitoring and control through networks of interconnected devices, effective handling of the associated rich data streams is becoming an important challenge. In many situations, the application of conventional system identification or approximate grey-box models, partly theoretic and partly data driven, is either unfeasible or unsuitable. The paper discusses and illustrates an application of black-box modelling achieved using data mining techniques with the purpose of smart building ventilation subsystem control. We present the implementation and evaluation of a data mining methodology on collected data from over one year of operation. The case study is carried out on four air handling units of a modern campus building for preliminary decision support for facility managers. The data processing and learning framework is based on two steps: raw data streams are compressed using the Symbolic Aggregate Approximation method, followed by the resulting segments being input into a Support Vector Machine algorithm. The results are useful for deriving the behaviour of each equipment in various modi of operation and can be built upon for fault detection or energy efficiency applications. Challenges related to online operation within a commercial Building Management System are also discussed as the approach shows promise for deployment.

Application of IoT in Zambia’s FRA Grain Traceability Process

<p class="0papersubtitle">with advancement in technology, many sectors have seen growth and improvement in service delivery. Today, many areas such as health, transport and logistics, retailing among others have adopted the use of IoT. Agricultural sector has not been left out on the use of IoT. IoT is defined as a network of interconnected devices which can transfer data efficiently without human involvement. In agriculture, IoT can play a big role in increasing productivity and efficient storage management. Other applications include security, real-time object tracking and monitoring. In Zambia however, the agricultural sector through the Food Reserve Agency (FRA) while still underdeveloped, faces many challenges that range from spoilage, infestations, theft at site, spillage and storage among others. As the national food security agency, FRA has for many years been grappling with these challenges. In order to help curb theft problems, this study proposes the adoption of IoT and related technologies. The proposed IoT technologies will be a prototype model that will employ the use of GPS, RFID, PIR, Wireless radio communication module and the GSM technologies. The GPS will be used to monitor and track the location of the vehicle in transit using mobile and web applications. To curb theft of grain at stationary points, the system will use motion sensing through the use of PIR sensors, wireless radio communication module and the GSM/GPRS technologies. Lastly, RFID combined with GPRS and Arduino microcontroller will be responsible for grain bags tallying. </p><p class="0papersubtitle"> </p>

Supporting Distance Vector Routing Over Device Discovery Flows in the Pervasive Middleware PalCom

PalCom is a pervasive middleware that enables users to combine services from different devices into assemblies, or usage scenarios. The mechanism of device discovery in PalCom builds an ad-hoc network of interconnected devices while replacing cross-network periodic keep-alive messages with timely forwarded events that notify devices about the discovery and undiscovery of each other. Moreover, the device discovery mechanism is decoupled from any specific routing decisions mechanism. In this paper, we present a design that builds on this flexibility to add distance vector routing to PalCom while inheriting the event based cross-network device discovery for updating routing tables on interacting devices. The proposed design has been implemented and evaluated against a network with links that continuously change their availability.

DCT & DWT Images Compression Algorithms in Wireless Sensors Networks: Comparative Study and Performance Analysis

The recent availability of inexpensive hardware has enabled the new research field of wireless sensor networks. This is a network of interconnected devices, capable of retrieving images from the environment. The nodes, in this type of network, have very limited resources, in terms of processing unit, bandwidth and energy. Efficient coding of the image content is therefore important. In Wireless Sensors Network, many image compression algorithms are used. Indeed, the most popular methods such as JPEG or JPEG2000 can yield higher energy consumption than when transmitting uncompressed images. However, the most of the compression algorithms are inapplicable on sensor nodes because the limitation in terms of memory as well as processor speed. To solve this problem, we use DWT and DCT image compression algorithm that allows an efficient tradeoff between energy consumption and image distortion. These experimental results demonstrated by the performance evaluation are in terms of image quality, execution time and memory space, as shown in this paper.

An IEC61499-based development approach for distributed industrial control applications

The IEC61499 standard proposes the function block (FB) model for the next generation of distributed control applications. This model defines the FB type to be the basic construct in this paradigm. A control application is considered as a network of interconnected instances of FB types. These applications can be executed on one device such as a multitasking programmable logic controller (PLC), but they are usually executed on a network of interconnected devices. In this paper 1 , a methodology for the development and deployment of IEC61499-based control applications on a network of interconnected devices is proposed. The methodology is based on a hybrid approach that integrates the unified modelling language (UML) with the FB model; to semi automatically generate the design diagram in the form of a network of interconnected FB instances. A heuristic-based approach is described to allocate these instances to the execution environment, so as to satisfy constraints imposed by this kind of applications. A formal description of FB design models is proposed and a formal approach is described to assign FB instances to feasible OS tasks of devices while considering temporal constraints. A running example from industry is used to demonstrate the feasibility of the proposed approach.