Cloud-based Internet Of Things Research Articles

Privacy in a Smart City

An increasing number of cities around the globe aim to become Smart Cities through the implementation of a range of Information and Communication technologies (ICT), AI applications and cloud-based IoT solutions. While the underlying motivations vary, all such transitions require large amounts of data. In this paper, we articulate and defend two claims about privacy in a Smart City. Our first claim is that some level of systematic data collection and processing is ethically permissible. However, there is an upper limit for what is permissible: We suggest that it is never permissible to collect and process data that significantly undermine people’s autonomy. Our second claim specifies when such minor privacy infringements that do not significantly undermine people’s autonomy are permissible: We suggest that the only policies legitimized by the first claim are those that promote the collective good. Keywords: smart city, privacy, autonomy, natural right, collective good

Research on Task Scheduling for Internet of Things Cloud Computing Based on Improved Chicken Swarm Optimization Algorithm

Aiming at the shortcomings of long completion time and high consumption cost of cloud computing batch task scheduling in IoT, an Improved Chicken Swarm Optimization Algorithm (ICSO) for task scheduling in cloud computing scenarios is proposed. Specifically, in order to solve the problems of slow convergence and falling into local optimum of the chicken swarm optimization algorithm, we adopt the nonlinear decreasing technique of the rooster and the weighting technique of the hen, optimize the following coefficients of the chicks, and apply ICSO to cloud computing task scheduling. In simulation experiments, we conducted a large number of experiments using four standard benchmark functions with different number of tasks and the results show that ICSO algorithm reduces 25.8%, 9.3%, 8.8%, 7.5% in small task time compared to CSO, DCSO, GCSO, ABCSO in large task time by 30.8%, 8.3%, 7.8%, 6.3%, 11.8%, 10.3%, 8.8%, 7.5% savings in small task cost and 25.8%, 11.2%, 10.8%, 9.3% savings in large task cost. This method effectively reduces task scheduling time and cost consumption. Meanwhile, we tested it in combination with an IoT-based cloud platform and achieved very satisfying Results.

A Novel and Low-Cost Cloud-Enabled IoT Integration for Sustainable Remote Intravenous Therapy Management

Intravenous therapy is the standard medical procedure that is used for administering medications directly into the vein. The automated drug infusion devices are designed in such a way that they provide exact medication doses with safety measures included. On the other hand, this is why they must be regularly watched by healthcare providers. This paper introduces a cloud-based IoT drug infusion system that was developed to address remote patient care needs. This system enables remote, accurate, and secure management of medication delivery. Its key contributions include allowing healthcare providers to control and monitor IV infusions remotely while maintaining safety features. The system consists of a microcontroller that is responsible for data processing, a control system that oversees infusion rate regulation, and an IoT-based framework that allows for remote monitoring and alerts via a user-friendly web interface. This new approach to care will therefore improve patient care by providing remote management of medications.

Monitoring and Detecting Plant Diseases Using Cloud-Based Internet of Things

The farming field is currently going through an upheaval as a consequence of the Internet of Things (IoT), which is offering farmers a respectable spectrum of tackles that include precision and sustainable agriculture for confronting problems within the industry. IoT technology is used to obtain data on ambient conditions which include soil moisture, air temperature, and atmospheric moisture that are advantageous to the enhancement of the various microorganisms and the propagation of farm-related problems. Farmers' ambition to connect through their farms from any location around the globe at any time is fostered by IoT. Wirelessly connected devices record the situation of the farm, and microcontrollers are implemented to automate and regulate farm operations so that conditions may be observed remotely. Farmers can leverage IoT on their mobile devices to be warned about the ongoing state of their cultivated land at any time and at nearly any point across the world. IoT technology can help traditional farming become more profitable while lowering the hurdles it faces. Farmers possess real-time access to the details, which allows them to determine a health condition that originates from favorable ambient conditions. Farmers subsequently become professionals at sustaining the ecosystems of their crops. Furthermore, farming industries necessitate greater numbers of workers and more staff people. Unfortunately, a rising number of human beings are departing the agriculture industry, which has rendered the lack of employees severe. As an outcome, intelligent agricultural technologies are essential in agriculture to shrink the amount of workforce demanded while providing the rising requirements imposed by rising populations.

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.

Fog Computing-Based Smart Consumer Recommender Systems

The latest effort in delivering computing resources as a service to managers and consumers represents a shift away from computing as a product that is purchased, to computing as a service that is delivered to users over the internet from large-scale data centers. However, with the advent of the cloud-based IoT and artificial intelligence (AI), which are advancing customer experience automations in many application areas, such as recommender systems (RS), a need has arisen for various modifications to support the IoT devices that are at the center of the automation world, including recent language models like ChatGPT and Bard and technologies like nanotechnology. This paper introduces the marketing community to a recent computing development: IoT-driven fog computing (FC). Although numerous research studies have been published on FC “smart” applications, none hitherto have been conducted on fog-based smart marketing domains such as recommender systems. FC is considered a novel computational system, which can mitigate latency and improve bandwidth utilization for autonomous consumer behavior applications requiring real-time data-driven decision making. This paper provides a conceptual framework for studying the effects of fog computing on consumer behavior, with the goal of stimulating future research by using, as an example, the intersection of FC and RS. Indeed, our conceptualization of the “fog-based recommender systems” opens many novel and challenging avenues for academic research, some of which are highlighted in the later part of this paper.

Cloud-Based IoT Solutions for Smart Cities

Cloud-Based IoT Solutions for Smart Cities

IoT-based health monitoring and fault detection of industrial AC induction motor for efficient predictive maintenance

This research paper presents the development and implementation of an integrated condition monitoring and fault detection system for AC induction motors using a combination of sensors, GSM communication, and a cloud-based Internet of Things (IoT) platform. The proposed system aims to enhance industrial motors’ operational reliability and efficiency by providing real-time data monitoring and early fault detection. The key components of the system include temperature, vibration, current, voltage, and speed sensors, which are strategically placed to gather critical motor performance data. These sensors feed data to an Arduino-based control unit responsible for sensor data acquisition and processing. To ensure timely response to anomalies, the system is equipped with an alarm system and GSM alerts, which notify designated personnel in case of abnormal motor behavior. Moreover, the paper incorporates remote monitoring capabilities, enabling users to access motor health data and real-time status from a distance. Historical data is also stored for analysis and comparison through the integration of a cloud-based Blynk-IoT platform. Additionally, the system facilitates RPM control and utilizes relay modules for seamless motor control and protection. The proposed system was tested and validated using Proteus for circuit diagram simulation and Arduino for sensor coding. The results demonstrate its effectiveness in detecting abnormal motor behavior and its potential to prevent catastrophic failures by enabling predictive maintenance. The proposed system successfully detects and displays abnormalities in important parameters like vibration, temperature, speed, three-phase currents, and voltages with 99% accuracy.

Enhancing Microbial Fuel Cell Performance Prediction and IoT Integration Using Machine Learning and Renewable Energy

This study aims to enhance Microbial Fuel Cells (MFCs) reliability for remote environmental monitoring, emphasizing unexplored facets of accurate energy prediction and the integration of renewable energy-powered Internet of Things (IoT) devices. Following comprehensive research, design, and component procurement, an innovative and cost-effective IoT system was developed, leveraging renewable energy from MFCs. Using an Arduino UNO-WiFi, data was collected and showcased on a web page while logged in a Google Firebase database, with an Android app created for intuitive smartphone visualization. Over four months, sensor data was accumulated. An Artificial Intelligence (AI) model, employing Autoregressive Integrated Moving Average (ARIMA), precisely forecasted MFC energy production (RMSE: 0.0119 and 0.0113 for trials 1 and 2). Despite the initial energy production surge, a subsequent decline occurred due to organic matter depletion. This prototype represents an affordable and sustainable solution for cloud-based IoT environmental monitoring with AI-driven energy forecasts, embodying innovation in renewable energy applications and sustainable practices.

Security and Privacy of Wearable Wireless Sensors in Healthcare: A Systematic Review

Wearable Wireless Sensor Network (WWSN) devices are widely used in healthcare to monitor health data. However, when WWSN users transmit their data to healthcare professionals or third parties over wireless connections, they face privacy and security vulnerabilities. This paper aims to identify the unsolved privacy and security challenges in wearable sensor devices in healthcare, especially the aspects overlooked by previous research. The main research question is: What are the unsolved privacy and security challenges in wearable sensor devices in healthcare, and what are their implications for users and healthcare professionals? This systematic review employs specific keywords to search for relevant publications on bibliographic databases, including Google Scholar, Scopus, IEEE Xplore, and Web of Science. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) charts helped in screening and summarising the selected papers. The results highlight the critical areas that can make WWSNs vulnerable to security attacks. The findings examine the security and privacy issues of wearable sensor devices in cloud computing, fog computing, the Internet of Things (IoT) and the like. Many studies examine IoT due to its privacy and security challenges, especially regarding handling extensive data, using public channels, deploying advanced technologies, managing sharing policies alongside the growing number of wireless devices, and protecting data from hackers. These challenges seriously threaten the confidentiality, integrity, and availability of health data transmitted by WWSN users to healthcare professionals or third parties in cloud-based environments and IoT and are exacerbated by limited resources. The significant findings thereby focus on unresolved areas in IoT. This paper aims to safeguard against cyber-attacks on healthcare and increase users' adoption rate of WWSN devices.

A Novel Cloud-Based IoT Framework for Secure Health Monitoring

The growing use of Internet of Things (IoT) technologies in a variety of sectors, including healthcare, has opened up new possibilities for gathering and analyzing patient data. In some cases, the elderly are exposed to significant risk and even mortality as a result of the global aging problem, which has become a burden in recent years. Numerous IoT devices are being created to monitor, track, and record the actions of the elderly to reduce these hazards. This study proposed a novel, dependable, cloud-based remote system patient monitoring framework for IoT health detection. The main distinguished part of this research is that we rarely can find a framework in the literature that is based on real-time systems by considering heartbeat (BPM), blood oxygen (SpO2), and body temperature at the same time. The implementation and testing of this real-time system is classified into six distinctly separated phases for developing both the hardware and software. To verify the performance of the suggested system, data were gathered from BOT-IoT datasets. The outcome enhances patient satisfaction, secure data transmission, and healthcare outcomes by showing that the proposed framework is more efficient than other compared protocols in terms of the decision time, which is 16.3 seconds for 46 features, with 100% accuracy.

Design of battery state of charge monitoring and control system using coulomb counting method based

<span>Lead-acid batteries are commonly used in photovoltaic systems to store solar energy for continuous use. However, lead-acid batteries have a relatively short lifespan due to frequent over-charging and over-discharging. A battery management system (BMS) is essential for accurately predicting the battery state of charge (SoC) value in order to extend the battery lifespan. In this research, a BMS is developed using the coulomb counting method to estimate the SoC value of a lead-acid battery. The coulomb counting algorithm provides a reliable estimation of the battery’s SoC value by calculating the incoming and outgoing currents. The BMS also uses two normally closed relays to prevent overcharging and over-discharging. The first relay turns on when the SoC reaches 100% full charge and turns off when the SoC decreases to 70%. The second relay turns on when the SoC reaches 20%. The BMS was tested using Blynk, a cloud-based internet of things (IoT) platform. The results showed that the BMS successfully provided monitoring and reliable control of the lead-acid battery, with a low margin of error. This demonstrates that the developed BMS can be practically implemented in photovoltaic (PV)-battery systems to extend the battery lifespan and improve the overall performance of the system.</span>

Secure and Efficient Bloom-Filter-Based Image Search in Cloud-Based Internet of Things

Secure and Efficient Bloom-Filter-Based Image Search in Cloud-Based Internet of Things

Star-Quake: A New Operator in Multi-Objective Gravitational Search Algorithm for Task Scheduling in IoT-Based Cloud–Fog Computing System

Star-Quake: A New Operator in Multi-Objective Gravitational Search Algorithm for Task Scheduling in IoT-Based Cloud–Fog Computing System

Multi-replicas integrity checking scheme with supporting probability audit for cloud-based IoT.

Nowadays, more people are choosing to use cloud storage services to save space and reduce costs. To enhance the durability and persistence, users opt to store important data in the form of multiple copies on cloud servers. However, outsourcing data in the cloud means that it is not directly under the control of users, raising concerns about security and integrity. Recent research has found that most existing multicopy integrity verification schemes can correctly perform integrity verification even when multiple copies are stored on the same Cloud Service Provider (CSP), which clearly deviates from the initial intention of users wanting to store files on multiple CSPs. With these considerations in mind, this paper proposes a scheme for synchronizing the integrity verification of copies, specifically focusing on strongly privacy Internet of Things (IoT) electronic health record (EHR) data. First, the paper addresses the issues present in existing multicopy integrity verification schemes. The scheme incorporates the entity Cloud Service Manager (CSM) to assist in the model construction, and each replica file is accompanied with its corresponding homomorphic verification tag. To handle scenarios where replica files stored on multiple CSPs cannot provide audit proof on time due to objective reasons, the paper introduces a novel approach called probability audit. By incorporating a probability audit, the scheme ensures that replica files are indeed stored on different CSPs and guarantees the normal execution of the public auditing phase. The scheme utilizes identity-based encryption (IBE) for the detailed design, avoiding the additional overhead caused by dealing with complex certificate issues. The proposed scheme can withstand forgery attack, replace attack, and replay attack, demonstrating strong security. The performance analysis demonstrates the feasibility and effectiveness of the scheme.

A Review about Internet of Things (IoT) integration with Cloud Computing with a Limelight on Security

Cloud computing has become a pivotal and widely embraced technology due to its accessibility and cost-effectiveness. This review explores the intersection of cloud computing and Internet-of-Things (IoT) devices, highlighting the remarkable advancements made in resource utilization and storage methods. However, this rapid growth has also raised concerns about security. Through an in-depth analysis of recent research, we examine the security challenges associated with IoT-based cloud computing, including account hacking, phishing, malware, middleman attacks, and service denial. We also discuss the potential benefits, architectural integration options, and the impact of IoT on cloud computing. This review paper categorizes findings and solutions from recent research papers, ultimately shedding light on the vulnerabilities and weaknesses of IoT-based cloud computing, along with its performance and stability issues.

A cloud-based IoT smart water distribution framework utilising BIP component: Jordan as a model

A cloud-based IoT smart water distribution framework utilising BIP component: Jordan as a model

A cloud-based IoT smart water distribution framework utilising BIP component: Jordan as a model

A cloud-based IoT smart water distribution framework utilising BIP component: Jordan as a model

Security aspects in IoT based cloud computing

Cloud computing offers a flexible framework in which data and resources are spread across different locations and can be accessed from various industrial environments. This technology has revolutionized the way resources such as data, services, and applications are used, stored, and shared in industrial applications. Over the past decade, industries have rapidly embraced cloud computing due to its advantages of enhanced accessibility, cost reduction, and improved performance. Moreover, the integration of cloud computing has led to significant advancements in the field of the Internet of Things (IoT). However, this quick shift to the cloud has also introduced various security concerns and challenges. Traditional security solutions are not always suitable or effective for cloud-based systems. Despite the continuous use of complex cyber weapons, efforts have been made in recent years to address the security issues and concerns associated with cloud platforms. The rapid progress of deep learning (DL) in the field of artificial intelligence (AI) has provided opportunities to tackle these security challenges in the cloud. The research presented in this study encompasses a comprehensive survey of the enabling architecture, services, configurations, and security models for cloud-based IoT. It also categorizes the security concerns in IoT within four major categories (data, network and service, applications, and people-related security issues) and provides a detailed discussion on each category. Furthermore, the study examines the latest advancements in cloud-based IoT attacks, analyzes significant security issues within each category, and presents the limitations from a broader perspective encompassing general, artificial intelligence, and deep learning aspects.

Flying Trap (Fly-T): An Automatic Termite Trapping Based on IoT and Hybrid Energy System using NodeMCU

This paper proposes an automated productive caste termite trap device based on a hybrid energy system and the Internet of Things called Flying Trap (Fly-T). This tool is equipped with ultraviolet light with a frequency of 365 nm which is used to attract termites to enter and trap into Fly-T storage tank until they die. Dead termites will be detected by an ultrasonic sensor with a certain limit value then the relay cuts off electric current so that the light turns off and the tank door automatically opens to expel dead termites. The automatic control system on Fly-T is built using the NodeMCU ESP32 microcontroller to optimize the performance of sensors, relays, servo, and wifi connections in recording data to an IoT-based cloud database. The Fly-T is also controlled by command via a Telegram Bot equipped with solar panels and a windmill turbine generator. The results show that Fly-T can run automatically, easily, and save time efficiently, and is environmentally friendly.