Smart IoT Research Articles

Blockchain-based secure and smart healthcare IoT system using hybrid consensus mechanism with an honest block

Blockchain-based secure and smart healthcare IoT system using hybrid consensus mechanism with an honest block

Ferro-Electric RAM

Ferroelectric RAM (FRAM) is a promising non-volatile memory technology that combines the advantages of both DRAM and Flash memory. FRAM offers fast read and write speeds, low power consumption, and high endurance, making it suitable for a wide range of applications. It stores data by utilizing the ferroelectric properties of certain materials, which can retain their polarization even when the power is off. This allows FRAM to offer high-speed operation with low power consumption, making it ideal for use in IoT devices, smart cards, and automotive systems

Development of an Improved Solid Waste Management System in Nigeria Using Smart IOT Devices

Rapid rise in inhabitants across the globe has led to the inadmissible management of waste in various countries, giving rise to various health issues and environmental pollution. Waste management is a daily task in urban areas, which requires a large amount of labour resources and affects natural, budgetary, efficiency, and social aspects. Many approaches have been proposed and implemented in developed countries to optimize waste management, such as smart waste in and route optimization. However, these technologies are still new in developing countries and have been implemented fully. The waste-collecting trucks collect waste just once or twice in seven days. The poor and improper disposal of waste produces toxic gases, and radiation in the environment, which has adverse effects on human health. The agency managing waste in Nigeria lack proper coordination to ensure better result. These challenges motivated this research. The research develop an improved solid waste management system using IoT sensors. The robust web-based system, coordinate and manage all the trucks, drivers and revenue generated from waste disposal to ensure better result when compared with existing method. The methodology adopted for this system is Object Oriented System analysis and designed (OOAD) methodology for the web based system, and Embedded C++ is used for the algorithm that controls the sensor reading. However, the MQ5, MQ7, MQ135 and Load cell sensors were used for dumpsite monitoring. While Ardunino Controller and Sim808 Gate way are used for System connection and transmission. The result from the simulated work, shows that air quality and waste bin level can monitored concurrently, which boost the efficiency of the new system. Moreover, the incorporation of load cell sensor at the dumpsite also help the regulatory body to computing the efficiency of the evacuation process of truck drivers. The readings of gas sensors on air quality from simulated environment were compared with six membership performance index (MID) of WHO air quality standard. The result shows that the simulated dumpsites were able to capture five out of the six MID. This represents 83.33% compliance to the WHO standard. The Improved solid waste management system developed in this work will help for proper coordination of waste collection and disposal, to ensure a clean and healthy environment that provides transparency in the business of waste management upon its implementation Keywords: Development, Solid Waste, Management, Smart and IOT Devices

Agricultural waste rice husk/poly(vinylidene fluoride) composite: a wearable triboelectric energy harvester for real-time smart IoT applications

Agricultural waste rice husk/poly(vinylidene fluoride) composite: a wearable triboelectric energy harvester for real-time smart IoT applications

User-trust centric lightweight access control for smart IoT crowd sensing applications in healthcare systems

User-trust centric lightweight access control for smart IoT crowd sensing applications in healthcare systems

Smart IoT Solutions for Precise COVID-19 Lung and Heart Disease Identification via Bayesian Neural Networks and Hybrid Optimization

Smart IoT Solutions for Precise COVID-19 Lung and Heart Disease Identification via Bayesian Neural Networks and Hybrid Optimization

DermSegNet: smart IoT model for multi-class dermatological lesion diagnosis using adaptive segmentation and improved EfficientNetB3

DermSegNet: smart IoT model for multi-class dermatological lesion diagnosis using adaptive segmentation and improved EfficientNetB3

Retraction Note: Grid quorum-based spatial coverage for IoT smart agriculture monitoring using enhanced multi-verse optimizer

Retraction Note: Grid quorum-based spatial coverage for IoT smart agriculture monitoring using enhanced multi-verse optimizer

VARDARA: An Online IOT Based Water Delivery Application

This paper presents a novel online water and delivery system, "VARDARA," designed to address the pressing need for convenient and efficient water distribution. Our solution integrates an intuitive Android application with smart IoT vehicles to enable seamless online ordering and timely delivery of water. By optimizing delivery routes and leveraging IoT technology, we ensure quicker and more environmentally friendly deliveries, bridging the gap between e-commerce and efficient water distribution. This innovative approach enhances customer convenience and contributes to sustainable resource management. Key Words: water, delivery, online, IoT, efficiency, sustainability.

An Optimized Data Storage in A Secure Cloud-Edge Collaboration A Fault Tolerance Approach

The rise of edge smart IoT devices has led to the development of edge storage systems (ESS) for efficient access to massive edge data. ESS can reduce the load on cloud centers and improve user experience. However, ESS still faces challenges in improving fault tolerance and efficiency. Thus, there is a need for a secure and efficient fault-tolerant storage scheme. Existing schemes have drawbacks like high edge storage overhead, difficulty in protecting edge data privacy, and low data writing performance. To address these issues, we propose a Hierarchical Cloud-Edge Collaborative Fault-Tolerant Storage (HCEFT) model. This model aims to enhance system robustness, reduce edge storage overhead, and ensure edge data privacy. We also introduce an optimization method for data writing in HCEFT, called ECWSS (Erasure Code data Writing method based on Steiner tree and SDN). This method improves the trade-off between data writing time and traffic consumption. Our scheme improves data robustness, availability, and security. Additionally, the writing optimization method reduces data write time by 13%-67% and network traffic consumption by 20%-62%, enhancing network load balance performance.

Development of an IoT smart energy meter with power quality features for a smart grid architecture

Electricity consumption has been intensifying due to population growth, climate change, urbanization, and the growing use of electronic devices, which are increasingly non-linear loads that cause poor power quality conditions. The trend of the Internet of Things has led to the creation of devices that encourage the efficient and effective utilization of electrical power. This in turn facilitates the development of modern power distribution structures such as smart grids. Consequently, this paper presents in detail the design, construction, and validation of a three-phase IoT smart meter intended to form part of the end-user demand side of a smart grid. The compact embedded system, with a manufacturing cost below $80 USD, features a unique electronic design that enables its installation in any load center and employs a straightforward IoT structure that includes WiFi technology for Internet communication. Also, a deployed web application was developed specifically to display the smart meter measurements. Unlike other smart meters, the proposed meter not only provides the amount of active energy consumption, but total and fundamental RMS current and voltage, active, reactive, and apparent power, reactive energy, power factor, and some power quality parameters such as, line frequency, amplitude of 64 current harmonics, and total harmonic distortion. Additionally, this study shows that the prototype achieves an absolute error of less than 1% in all its measurements. Finally, real-life applications of the developed device are demonstrated in residential environments.

Analysis of the population density trend of the finless porpoise based on smart IoT technologies

AbstractWith the rapid expansion of human activities, natural environmental systems are under severe threat. Yangtze River, the largest river in China, contains abundant biological resources. However, the ecosystem of the Yangtze River has been threatened by the rapid rise of human activities due to economic development in the 1990s. The Yangtze finless porpoise Neophocaena phocaenoides asiaeorientalis is a critically endangered flagship species in the Yangtze River. Although scientists have conducted surveys studying the abundance of Yangtze finless porpoise, the length of the investigation period of these studies was restricted. Here, we reported our meta-analysis results by collecting data on the abundance of the Yangtze finless porpoise population from published papers over 33 years. We found that the pooled effect size using the random effect model across all these studies was – 0.36 (95% confident interval (CI) – 0.48,– 0.24, P < 0.05), indicating that the porpoise population has undergone a declining pattern after the year 2003. The operation of the Three Gorges Dam was one important but not the only factor resulting in the decline of the porpoise population. More actions should be taken for porpoise and habitat protection and more studies should be done to assess the impact of dams on the porpoise population in Poyang Lake. Only in this way can marine life be better protected, and the marine environment can better achieve sustainable development.

Design and Evaluation of a High-Efficiency Smart IoT Device Incorporating Embedded Tiny Machine Learning for Monitoring Asset Activity

Design and Evaluation of a High-Efficiency Smart IoT Device Incorporating Embedded Tiny Machine Learning for Monitoring Asset Activity

Enhancing quality-driven iot operations for smart cities: A comprehensive approach for routing, security, and optimization

This study introduces a tailored data acquisition and communication framework for IoT smart applications, focusing on enhancing efficiency and system performance. The proposed Quality-Driven IoT Routing (EQR-SC) for smart cities utilizes IoT-enabled wireless sensor networks. Additionally, a noteworthy contribution is the introduction of the Chaotic Firefly Optimization (CFOA) algorithm for IoT sensor cluster formation, potentially optimizing the organization and efficiency of IoT sensor networks in smart cities. Trust-based cluster Head Selection is enhanced by employing the Weighted Clustering Algorithm (WCA), which assigns weights to nodes based on trustworthiness and relevant metrics to select reliable cluster heads. The proposal of a lightweight data encryption technique enhances data security among IoT sensors, ensuring the privacy and integrity of transmitted information. To optimize pathfinding within the IoT platform, the research employs the Bellman-Ford algorithm, ensuring efficient data routing while accommodating negative edge weights when necessary. Finally, a thorough performance analysis, conducted through network simulation (NS2), provides insights into the effectiveness of the proposed OQR-SC technique, allowing for valuable comparisons with existing state-of-the-art methods.

E-government impact on developing smart cities initiative in Saudi Arabia: Opportunities & challenges

Information and communication technologies (ICT) have a recent impact on governance and public administration. Electronic government (e-government) services were created to streamline administrative processes and enhance citizen engagement on the one hand, and to build new governance models that would empower individuals, involve them in the decision-making process, and increase transparency on the other. Many individuals are doubtful about smart city projects because of the security issues that arise in such environments. In essence, internet of things gadgets are security flaws. Concerns about the proliferation of IoT sensors and the tighter coupling of infrastructure silos in cities are well-founded. The major objective of the study is to identify the influencing factors of smart cities on e-government in Saudi Arabia. Additionally, this research explores the definition of e-government, and its supporting technologies like smart cities, IoT, big data, cloud computing and other digital government platforms. After exploring the detailed definitions, the study identifies the challenging scenarios of e-government in Saudi Arabia, and discusses the different opportunities. This study also concentrates on the good practices to be followed to overcome the challenges. Furthermore, this study can be used in future research for solving real time challenges of e-government.

ServeItNow - Home Services Made Easy

Abstract: ServeItNow, an innovative online household service platform, is revolutionizing the way people access and engage with home services. This abstract provides an overview of how ServeItNow simplifies the lives of both homeowners and service providers. ServeItNow acts as a bridge connecting users with a diverse array of local service providers, including plumbers, electricians, cleaners, and movers. The platform's core mission is to provide a seamless, convenient, and trustworthy way for individuals to find and book essential household services. One of the standout features of ServeItNow is its user-friendly interface. With just a few clicks or taps, users can effortlessly navigate through a directory of local service providers, read authentic reviews from fellow customers, and select the services that precisely match their needs. This intuitive approach has made ServeItNow a preferred choice for users seeking reliable and efficient household services.In the world of online services, trust is paramount, and ServeItNow recognizes this importance. The platform employs stringent verification processes to ensure that all registered service providers are qualified, competent, and dependable. Moreover, users have the ability to contribute to transparency and accountability within the community by leaving reviews and ratings for the services they receive. For service providers, ServeItNow offers a valuable platform to showcase their skills and expand their client base. By establishing a digital presence and accumulating positive reviews, service providers can enhance their credibility and grow their businesses within the ServeItNow community. Market trends indicate that ServeItNow is part of a larger trend in the online household service sector, which is experiencing substantial growth. The presence of competition is driving innovation and raising the bar for service quality. To stay ahead, ServeItNow continually enhances its features and offerings to meet evolving user needs. Technology plays a pivotal role in ServeItNow's success. The platform's mobile app ensures users can access services conveniently, even while on the move. Furthermore, ServeItNow explores the potential integration of smart devices and IoT technology to further streamline service delivery and elevate user experiences. In conclusion, ServeItNow stands as a transformative force in the realm of household services. It simplifies the process of discovering, booking, and receiving dependable home services. Its commitment to trust, transparency, and user-friendliness benefits both homeowners and service providers. As technology continues to evolve, and competition drives innovation, platforms like ServeItNow are poised to shape the future of home services, offering homeowners a seamless and stress-free experience and creating new opportunities for service professionals.

A Raspberry Pi-Powered IoT Smart Farming System for Efficient Water Irrigation and Crop Monitoring

Water irrigation remain as a challenge to supply adequate amount of water to sustain the growth of plant and crops yield along the year in certain part of the world which are heavily affected by climate change. This scenario creates a huge risk toward the world food supply chain. Hence, the application of smart farming system is crucially important now to pave the way for a better the agriculture monitoring system to replace traditional manual monitoring labour by farmers. The smart farming system are usually equipped with environmental stimuli sensing system such as temperature, humidity, soil moisture, light intensity sensing sensors coupled with automation actuators to control the water irrigation rate for the crops in order to save water and at the same time provide adequate water supply for plant growth. The aim of using such smart farming system is to enable higher crops production and less human labour at the same time optimising resources available to minimize cost of farming. Hence, this paper aims to introduce a novel approach of a Raspberry Pi powered IoT smart farming system (ISFS) which can incorporate autonomous monitoring of plant irrigation, temperature, humidity, soil moisture and light intensity, to design a smartphone app that allows users to monitor plantation-related conditions in a user-friendly manner, and to enable automatic control of a drip irrigation system for plants based on data obtained on soil moisture, temperature and sunlight intensity. The proposed prototype with the functionality mentioned is aim to resolve the existing problem and to meet the demand of smart farming application in current era.

An Efficient Edge Computing-Enabled Network for Used Cooking Oil Collection.

In Portugal, more than 98% of domestic cooking oil is disposed of improperly every day. This avoids recycling/reconverting into another energy. Is also may become a potential harmful contaminant of soil and water. Driven by the utility of recycled cooking oil, and leveraging the exponential growth of ubiquitous computing approaches, we propose an IoT smart solution for domestic used cooking oil (UCO) collection bins. We call this approach SWAN, which stands for Smart Waste Accumulation Network. It is deployed and evaluated in Portugal. It consists of a countrywide network of collection bin units, available in public areas. Two metrics are considered to evaluate the system's success: (i) user engagement, and (ii) used cooking oil collection efficiency. The presented system should (i) perform under scenarios of temporary communication network failures, and (ii) be scalable to accommodate an ever-growing number of installed collection units. Thus, we choose a disruptive approach from the traditional cloud computing paradigm. It relies on edge node infrastructure to process, store, and act upon the locally collected data. The communication appears as a delay-tolerant task, i.e., an edge computing solution. We conduct a comparative analysis revealing the benefits of the edge computing enabled collection bin vs. a cloud computing solution. The studied period considers four years of collected data. An exponential increase in the amount of used cooking oil collected is identified, with the developed solution being responsible for surpassing the national collection totals of previous years. During the same period, we also improved the collection process as we were able to more accurately estimate the optimal collection and system's maintenance intervals.

Behavioral equivalences for AbU: Verifying security and safety in distributed IoT systems

Attribute-based memory Updates (▪in short) is an interaction mechanism recently introduced for adapting the Event-Condition-Action (ECA) programming paradigm to distributed reactive systems, such as autonomic and smart IoT device ensembles. In this model, an event (e.g., an input from a sensor, or a device state update) can trigger an ECA rule, whose execution can cause the state update of (possibly) many remote devices at once; the latter are selected “on the fly” by means of predicates over their state, without the need of a central coordinating entity.However, the combination of different ▪systems may yield unexpected interactions, e.g., when a new device is added to an existing secure system, potentially hindering the security of the whole ensemble of devices. This can be critical in the IoT, where smart devices are more and more pervasive in our daily life.In this paper, we consider the problem of ensuring security and safety requirements for ▪systems (and, in turn, for IoT devices). The first are a form of noninterference, as they correspond to avoid forbidden information flows (e.g., information flows violating confidentiality); while the second are a form of non-interaction, as they correspond to avoid unintended executions (e.g., leading to erroneous/unsafe states).In order to formally model these requirements, we introduce suitable behavioral equivalences for ▪. These equivalences are generalizations of hiding bisimilarity, i.e., a kind of weak bisimilarity where we can compare systems up to actions at different levels of security. Leveraging these behavioral equivalences, we propose (syntactic) sufficient conditions guaranteeing the requirements and, then, effective algorithms for statically verifying such conditions.

A Comprehensive Analysis and Visualization of Trends and Research Patterns in the Field of IoT Smart Cities

Every nation is interested in creating "smart cities," making this a hot topic requiring extensive scientific study. Given the current state of affairs, it is essential to conduct a systematic review to thoroughly understand the current research trends and patterns in this field. It is applied to a corpus of 9,131 papers published between 2010 and 2022 from the Scopus publications database to test the string's effectiveness. This research utilizes text mining and Latent Semantic Analysis (LSA) to delve into the current state-of-the-art study concerning IoT Smart cities research. KNIME was used to conduct the analysis. Predicting the study domain is done with the help of the K-means clustering method. Future researchers can build upon these patterns to strengthen security in various sectors. This report also reviews the history of smart city research, its current position, and its prospects. We help institutions and authors collaborate globally in science. This research analyses Smart City IoT integration trends and patterns in a graphical overview. According to the data, the identified areas are developing and need more research.