Internet Of Things Innovation Research Articles

Recent advances in fish cutting: From cutting schemes to automatic technologies and internet of things innovations.

Fish-cutting products are widely loved by consumers due to the unique nutrient composition and flavor in different cuts. However, fish-cutting faces the issue of labor shortage due to the harsh working environment, huge workload, and seasonal work. Hence, some automatic, efficient, and large-scale cutting technologies are needed to overcome these challenges. Accompanied by the development of Industry 4.0, the Internet of Things (IoT), artificial intelligence, big data, and blockchain technologies are progressively applied in the cutting process, which plays pivotal roles in digital production monitoring and product safety enhancement. This review focuses on the main fish-cutting schemes and delves into advanced automatic cutting techniques, showing the latest technological advancements and how they are revolutionizing fish cutting. Additionally, the production monitoring architecture based on IoT in the fish-cutting process is discussed. Fish cutting involves a variety of schemes tailored to the specific characteristics of each fish cut. The cutting process includes deheading and tail removal, filleting, boning, skinning, trimming, and bone inspection. By incorporating sensors, machine vision, deep learning, and advanced cutting tools, these technologies are transforming fish cutting from a manual to an automated process. This transformation has significant practical implications for the industry, offering improved efficiency, consistent product quality, and enhanced safety, ultimately providing a modernized manufacturing approach to fish-cutting automation within the context of Industry 4.0.

Blockchain Enabled Secure Data Transmission With NB‐IoT Deployment in Smart Agriculture Crop Watch

ABSTRACTThe integration of Narrowband Internet of Things (NB‐IoT) and blockchain technology presents a promising solution to address security and efficiency concerns in data transmission within the Internet of Things (IoT). This research focuses on its application in crop Watch, an agricultural monitoring system. The IoT has revolutionized various industries, including agriculture, by facilitating the collection and transmission of extensive data through sensors and devices. However, ensuring secure and efficient data transmission remains a critical challenge. NB‐IoT boasts advantages such as improved coverage in challenging areas, massive connectivity with up to 100 000 links, low energy usage through prolonged discontinuous receipt (eDRX), and cost‐effectiveness. Despite these benefits, NB‐IoT faces security issues, including authentication, anonymity, and fault tolerance. To enhance data security, public key cryptography is proposed to be incorporated into the NB‐IoT framework. Blockchain technology, with its decentralized and immutable nature, can potentially address these security concerns and enhance data accountability. By creating a trust‐less and transparent infrastructure, blockchain complements NB‐IoT's capabilities and provides a robust mechanism for data verification and integrity. This research paper emphasizes the logical integration of NB‐IoT, public key cryptography, and blockchain technology, offering a secure and efficient data transmission framework for agricultural applications like crop Watch. Bridging the gap between data connectivity and security holds promise for advancing agricultural monitoring and driving IoT innovations.

Internet of Things-Driven Precision in Fish Farming: A Deep Dive into Automated Temperature, Oxygen, and pH Regulation

The research introduces a revolutionary Internet of Things (IoT)-based system for fish farming, designed to significantly enhance efficiency and cost-effectiveness. By integrating the NodeMcu12E ESP8266 microcontroller, this system automates the management of critical water quality parameters such as pH, temperature, and oxygen levels, essential for fostering optimal fish growth conditions and minimizing mortality rates. The core of this innovation lies in its intelligent monitoring and control mechanism, which not only supports accelerated fish development but also ensures the robustness of the farming process through automated adjustments whenever the monitored parameters deviate from desired thresholds. This smart fish farming solution features an Arduino IoT cloud-based framework, offering a user-friendly web interface that enables fish farmers to remotely monitor and manage their operations from any global location. This aspect of the system emphasizes the importance of efficient information management and the transformation of sensor data into actionable insights, thereby reducing the need for constant human oversight and significantly increasing operational reliability. The autonomous functionality of the system is a key highlight, designed to persist in adjusting the environmental conditions within the fish farm until the optimal parameters are restored. This capability greatly diminishes the risks associated with manual monitoring and adjustments, allowing even those with limited expertise in aquaculture to achieve high levels of production efficiency and sustainability. By leveraging data-driven technologies and IoT innovations, this study not only addresses the immediate needs of the fish farming industry but also contributes to solving the broader global challenge of protein production. It presents a scalable and accessible approach to modern aquaculture, empowering stakeholders to maximize output and minimize risks associated with fish farming, thereby paving the way for a more sustainable and efficient future in the global food supply.

The evolution of Internet of Things (IoT) research in business management: a systematic review of the literature

PurposeThis paper systematically reviews the evolution of Internet of Things (IoT) research in business and management over the past decade and a half. It synthesizes current knowledge, identifies major themes, gaps, and future opportunities to guide scholars on potential research directions within this exponentially growing domain.Design/methodology/approachA structured systematic literature review methodology filtered IoT publications across business/management journals using Scopus database. Detailed thematic and bibliometric analyses chronologically mapped the progress of peer-reviewed articles from 2005–2023. Both quantitative metrics and qualitative coding inductively revealed historical trends, topics, applications and research implications.FindingsAnalysis uncovered six primary IoT research themes - business models, technology, data, customers, organizations, and sustainability. Dominant focuses were found on technological enablers, business model innovation and customer experience transformations. While technical aspects are well-documented, strategic technology integrations and organizational change management require greater emphasis.Research limitations/implicationsFocus restricted to academic articles published in management journals risks missing relevant papers published in other fields. Screening process involved some subjectivity. Lacks geographic analysis of research contexts. The rapidly evolving nature of technology domain risks findings’ generalizability.Practical implicationsKey enablers and success factors that we identified may support managerial decision making when it comes to IoT adoption.Social implicationsWe discuss advancing IoT innovation through ethics and sustainability lenses and these may help ensure responsible adoption.Originality/valueThis analysis weaves together the extant literature and offers an evidence-based research agenda for management scholars by chronicling the state, evolution, influential factors, and future opportunities within IoT literature. It highlights major thematic shifts and priority gaps to address.

Innovations in Internet of Things: Challenges and Opportunities

Innovations in Internet of Things: Challenges and Opportunities

Revolutionizing indoor air quality monitoring through IoT innovations: a comprehensive systematic review and bibliometric analysis.

Indoor air quality (IAQ) in the built environment is significantly influenced by particulate matter, volatile organic compounds, and air temperature. Recently, the Internet of Things (IoT) has been integrated to improve IAQ and safeguard human health, comfort, and productivity. This review seeks to highlight the potential of IoT integration for monitoring IAQ. Additionally, the paper details progress by researchers in developing IoT/mobile applications for IAQ monitoring, and their transformative impact in smart building, healthcare, predictive maintenance, and real-time data analysis systems. It also outlines the persistent challenges (e.g., data privacy, security, and user acceptability), hampering effective IoT implementation for IAQ monitoring. Lastly, the global developments and research landscape on IoT for IAQ monitoring were examined through bibliometric analysis (BA) of 106 publications indexed in Web of Science from 2015 to 2022. BA revealed the most significant contributing countries are India and Portugal, while the top productive institutions and researchers are Instituto Politecnico da Guarda (10.37% of TP) and Marques Goncalo (15.09% of TP), respectively. Keyword analysis revealed four major research themes: IoT, pollution, monitoring, and health. Overall, this paper provides significant insights for identifying prospective collaborators, benchmark publications, strategic funding, and institutions for future IoT-IAQ researchers.

IOT Garbage Monitoring System with Weight Sensing

This paper presents a novel approach towards efficient waste management utilizing Internet of Things (IoT) technology. The proposed system integrates garbage monitoring and weight sensing capabilities to create a smart waste management solution. Traditional waste collection methods are often inefficient and lack real-time monitoring, leading to overflows, environmental hazards, and unnecessary resource allocation. By employing IoT sensors embedded within garbage bins, real-time data on fill-level and weight can be collected and transmitted to a central server. AI calculations are applied to break down the information and predict future fill levels, optimizing waste collection schedules and routes. The system also includes a command-line interface available through web or mobile applications, enabling users to request timely pickups or report issues. Furthermore, the weight sensing functionality provides insights into the type and volume of waste being generated, facilitating better waste categorization and recycling initiatives. Field tests conducted in urban environments demonstrate the adequacy of the proposed system, reducing operational costs, minimizing environmental impact, and enhancing overall waste management efficiency. The coordination of IoT innovation with garbage monitoring and weight sensing represents a significant advancement towards sustainable and smarter cities

IoT Innovations as a Strategy for Minimizing Construction Expenses

The revolutionary impact of Internet of Things (IoT) improvements on the construction enterprise is carefully tested on this extensive research, with a focus on cost-cutting strategies. Examining a wide range of IoT programs from the predictive repair of equipment to the actual-time monitoring of building materials the study highlights how those packages can appreciably lessen operating charges. This inquiry identifies key areas wherein IoT technology are expected to sell cost-saving measures by utilizing a thorough evaluation of relevant literature along with a robust method that includes case research and empirical records evaluation. Using 12 records points and a aggregate of documentation evaluation and interviews, this examine assesses the impact of IoT technology on constructing charges. It offers insights into how IoT adoption in creation might be financially viable with the aid of highlighting the way it influences fee dynamics and undertaking control. The observe concludes with the aid of dropping mild at the broader implications of IoT adoption inside the construction enterprise and emphasizing how important it is to promoting a sustainable environment and strengthening the competitive fringe of companies on this zone. The present investigation not only emphasizes the economic blessings of implementing IoT, but additionally indicates its capability to convert conventional building methods by way of facilitating the improvement of greater reasonably priced, efficient, and environmentally friendly venture execution strategies.

Sustainable manufacturing through empowering machine tools with IoT innovations: a literature review

In the 21st century, sustainability takes the front seat as one of the main objectives while designing and developing new technologies. Machine tools have significant contributions in fuelling all four industrial revolutions. One of the major stepping stones to the fifth Industrial Revolution is making these machine tools sustainable. In this paper, we review the major developments driven by the integration of internet of things (IoT) in the field of machine tools which contribute to achieving a sustainable future. This integration of IoT in machine tools is also significant in contributing to different sustainable development goals of the United Nations. Through this work, we aim to reach a better understanding of current improvements in machine tool operations and ecosystem achieved through IoT innovations. The future research directions that are opening in this domain and their scope and limitations are also covered.

Exploring the Impact and Future of the Internet of Things: A Comprehensive Review

A revolutionary force altering many facets of our everyday lives, industries, and communities is the Internet of Things (IoT). This in-depth analysis seeks to assess the diverse effects of IoT technologies and provide predictions about their future developments. We examine the state of IoT applications already available in industries like manufacturing, smart cities, transportation, healthcare, and agriculture, emphasising the advantages, difficulties, and new developments. We also explore the technology developments, such as blockchain, edge computing, and artificial intelligence, that are propelling IoT innovation. We also go over important issues with security, privacy, interoperability, and ethical ramifications of the growing number of IoT devices. In conclusion, we offer perspectives on the future course of the Internet of Things, imagining a state in which human endeavours are harmoniously merged with interconnected ecosystems, promoting effectiveness, durability, and improved user experiences. This assessment adds to a better understanding of the Internet of Things' revolutionary potential and alerts stakeholders to the opportunities and difficulties associated with using this disruptive technology to enhance society.

SMART FARMING DECISION SUPPORT SYSTEM FOR PRECISION AGRICULTURE

The incorporation of IoT (Internet of Things) innovation within agricultural practices, often referred to as precision agriculture, has gained significant attention in recent years. This paper presents the development and implementation of a Smart Farming Decision Support System aimed at enhancing agricultural efficiency, productivity, designed to optimize water management and resource utilization in precision agriculture. The system utilizes various sensors, microcontrollers, and web technologies to monitor environmental conditions and automate irrigation processes in real-time. A detailed description of the system architecture along with its hardware components, software implementation, deployment strategy, experimental results, and potential impact on agricultural practices is provided.

Model Exploration of Enhancing the Effectiveness of College Students’ Innovation and Entrepreneurship Based on Internet of Things Technology

Abstract How to use the Internet of Things (IoT) technology to enhance the effectiveness of innovation and entrepreneurship of college students has become a topic of focus in undergraduate colleges and universities. For this reason, this paper proposes to integrate innovation and entrepreneurship education with IoT technology. Due to the inconsistent application direction of IoT technology, it can be broken down into system integration technology, wireless communication technology, and intelligent sensing technology. These three are working together to create an innovative entrepreneurship teaching model that is based on IoT technology. The empirical analysis shows that the experimental group and the control group at the end of the period show large differences in the factor of innovation and entrepreneurship knowledge, with the mean values of 4.822, 5.163, and T=6.47, respectively, and P=0.0004. In addition, the linear regression equation of IoT technology and innovation and entrepreneurship ability (Y2) is Y2=71.863+0.128X1, which shows that IoT technology can effectively improve the students’ college students’ innovation and entrepreneurship knowledge, ability, and thinking. This study confirms that the development of IoT will bring unlimited possibilities to innovation and entrepreneurship education and will become an important driving force for developing students’ creative thinking.

Revolutionizing Tourism: Harnessing the Power of IoT in Smart Destinations

The convergence of technology and travel has given rise to the paradigm of smart destinations, fueled by the transformative force of the Internet of Things (IoT). This review paper delves into the revolutionary impact of IoT on tourism, specifically focusing on the concept of smart destinations. Smart Hotels, exemplifying this paradigm shift, redefine the guest experience through seamless technology integration. Smart room controls, driven by IoT, intuitively respond to guest preferences, transforming the traditional stay into a personalized and efficient encounter. Transportation undergoes a parallel transformation through connected transportation, where IoT innovations reshape global mobility. From smart airports to intelligent traffic management systems, the integration of IoT ensures seamless and efficient travel experiences for both passengers and goods. Wearable devices further enhance the tourism experience, with smart tour guides leading the way. Wearables provide real-time information and personalized recommendations, with smart glasses employing augmented reality (AR) to overlay digital information onto the physical world. This hands-free approach enriches tourist exploration of historical sites and museums. In popular tourist attractions, IoT-enabled experiences redefine engagement. From smart museums to AR tours and interactive exhibits, the integration of IoT technologies enhances how visitors interact with cultural landmarks, creating immersive and technologically enriched tourism experiences. This review explores the multifaceted intersections of IoT and tourism, offering insights into current trends and future prospects in this dynamic space.

Performance of matrix completion approaches for aquaponics data

Technological innovations in Internet of Things (IoT) have resulted in smart agricultural solutions such as a remotely monitored Aquaponics system and a wireless sensor network (WSN) of such systems (nodes). IoT enables continuous sensing of temperature and pH data at each node of the WSN, which is periodically transmitted to a remote fusion centre. In this regard, the data matrices acquired at the fusion centre often suffer from data vacancies and missing data problems, owing to typical wireless multipath fading environment, sensor malfunctions and node failures. This paper explores the applicability of different matrix completion approaches for missing data reconstruction. Specifically, the performance of baseline predictor, correlation based approaches such as baseline predictor with temporal model, k-nearest neighbors (kNN) and low rank based approaches such as Sparsity Regularized Singular Value Decomposition (SRSVD) and Augmented Lagrangian Sparsity Regularized Matrix Factorization (ALSRMF) have been explored. Reliable temperature and pH data for 19 independent acquisition hours with 60 samples per hour are acquired at the fusion centre via Ultra High Frequency (UHF) transmission at 470 MHz and suitable pre-processing. Simulating different data integrity scenarios, the reconstruction error plots from each of these matrix completion approaches is extracted. A hybrid of kNN and baseline predictor with temporal model rendered a Mean Absolute Percentage Error (MAPE) of 1.75% for temperature and 0.86% for pH, at 0.5 data integrity. Further, with ALSRMF, which exploits the low rank constraint, the error reduced to 1.25% for temperature and 0.7% for pH, thus substantiating a promising approach for Aquaponics system data reconstruction.

Diffusion of the Internet-of-Things (IoT): A framework based on smart retail technology

Internet-of-Things (IoT) innovations are reconfiguring our societies and day-to-day lives. How do these new technologies enter our communities, and when they do, how do they complement or disrupt existing activity? This paper provides a framework for addressing these questions, building on a case study of the automated pizza vending machine that is proliferating in France. Relying on an exclusive and newly constructed database, we examine the diffusion of smart pizza vending machines across over 30,000 French communities. Contrary to our expectations, we find that neither the large, dense, and most connected urban centers nor the rural areas with limited access to food options are the first adopters of these machines. Instead, small but well-connected communities, with attractive consumer bases but which lack 24/7 amenities, are at the vanguard of the adoption of this "frugal" IoT innovation -- i.e., one that requires little capital investment but potentially meets widespread demand. Furthermore, we find that independent business owners and small entrepreneurs are the early adopters of the new technology, but they act as forerunners for larger corporate actors. Based on these findings, our proposed framework highlights the decentralized and bottom-up processes that give rise to the rapid penetration of frugal IoT technologies and their associated socio-economic effects.

Service Quality and After-Sales Service on IoT-Based Car User Satisfaction and Repeat Purchases Services in Indonesia

This study aims to determine the effect of service quality and after-sales service on the customer satisfaction of car users using IoT (Internet of Things) technology provided with their car purchase. Digital disruption has made manufacturers turn to digital services and marketing systems to discover and understand customer behavior. Using the Isaac and Michael formula a sample size 155 respondents was determined, and data were accordingly collected for processing via non-probability sampling techniques. Data were obtained from respondents matching the unique criteria of Indonesian users of cars with IoT innovation technology. Such cars now account for 10% of total new car sales. This study utilizes path analysis, revealing that customer satisfaction encourages loyal customers to buy new units. The main finding of the research is that a service system connected to the internet or smartphones makes users comfortable and can determine the future choice for product repurchases. Therefore, it is necessary to develop continuous emotional closeness with customers for future success.

An intelligent context-aware threat detection and response model for smart cyber-physical systems

Smart cities, businesses, workplaces, and even residences have all been converged by the Internet of Things (IoT). The types and characteristics of these devices vary depending on the industry 4.0 and have rapidly increased recently, especially in smart homes. These gadgets can expose users to serious cyber dangers because of a variety of computing constraints and vulnerabilities in the security-by-design concept. The smart home network testbed setup presented in this study is used to evaluate and validate the protection of the smart cyber-physical system. The context-aware threat intelligence and response model identifies the states of the aligned smart devices to distinguish between real-world typical and attack scenarios. It then dynamically writes specific rules for protection against potential cyber threats. The context-aware model is trained on IoT Research and Innovation Lab - Smart Home System (IRIL-SHS) testbed dataset. The labeled dataset is utilized to create a random forest model, which is subsequently used to train and test the context-aware threat intelligence SHS model's effectiveness and performance. Finally, the model's logic is used to gain rules to be included in Suricata signatures and the firewall rulesets for the response system. Significant values of the measuring parameters were found in the results. The presented model can be used for the real-time security of smart home cyber-physical systems and develops a vision of security challenges for Industry 4.0.

Design and Implementation of Artificial Intelligence-based Real-time Pothole Detection for IoT Smart Infrastructure

The Internet of Things (IoT) has been extensively deployed for Smart Cities due to its ability to process many different and heterogeneous end systems. The IoT innovation encourages artificial intelligence applications to process data. In Smart City infrastructure, the road is a critical component of transportation infrastructure that supports the economic, social, and cultural things of community life and various aspects of community life. Road conditions affect a variety of community activities. Good roads enhance comfort and support local businesses. However, many roads remain in bad condition, such as potholes. Various methods have been attempted to identify potholes, especially the two-dimensional imaging method. This paper proposes the real-time Artificial Intelligence detection of potholes using the Convolutional Neural Network (CNN), which leverages the Edge Tensor Processing Unit (TPU) with the MobileNet SSD v2. The system was set up on a Jetson Nano with a few extras, including a camera and GPS, to support the IoT infrastructure. Evaluation for the model consists of device implementation, model evaluation, GPS position deviation, and on-road implementation. The effectiveness is confirmed through experiments using a system test-bed that generates ideal mAP off 0.22 and recall values.

Cyber Security & IoT Vulnerabilities Threats Intruders and Attacks Research Review

The Internet of Things (IoT) is a system of various systems of hardware and software that is mostly dependent on online services and a variety of cutting-edge communication and sensing innovations. The introduction of 5G networks will see an increase in the global expansion of IoT, however security problems related to IoT innovation will additionally necessitate comprehensive analyses. This study will provide a comprehensive overview of the security difficulties in an Iot infrastructure, as well as current incidents of IoT technology assaults, interoperability used in IoT systems. For the inaugural study, all of the key aspects of IoT security are analysed and defined collectively. This study would be a great asset for prospective studies focusing on the creation of more secure IoT transmission methods for dealing with security and privacy in IoT.

Fuzzy logic system for drug storage based on the internet of things: a survey

<span lang="EN-US">The rapid development of internet of things (IoT) technology over the course of recent history has made it possible to connect a large number of smart things and sensors, as well as to establish an environment in which data can be seamlessly exchanged between them. This has led to an increase in the demand for data analysis and storage platforms such as cloud computing and fog computing. One of the application areas for the internet of things that has garnered a lot of interest from the business world, academic institutions, and the government is healthcare. The IoT and fuzzy logic are being used in the medical business to improve patient safety, the overall quality of care, and the overall efficiency of medical operations. The most important healthcare studies that are pertinent to pharmacies have been used as the basis for this research. The purpose of this research is to investigate recent advancements in medical modules, remotes, and detector patterns, as well as current innovations in IoT and fuzzy logic-based health care, and current policies from around the world, with the intention of determining how well they support the long-term growth of IoT and fuzzy logic in healthcare.</span>