The research study intends to understand the thematic dynamics of the internet of things (IoT), thereby aiming to address the general objective i.e. “To explore and streamline the IoT thematic dynamics with a focus on cross-cutting data mining, and IoT apps evidence-based publication trends”. To meet this objective, secondary research has been compiled as part of the analytic process. It was found from the research that IoT continues to evolve with significant degrees of proliferation. Complementary and
trailblazing data mining (DM) with more access to cloud computing platforms has catalyzed accelerating the achievement of planned technological innovations. The outcome has been myriads of apps currently used in different thematic landscapes. Based on available data on app searches by users, and between 2016 and 2019, themes like sports, supply chain, and agriculture maintained positive trends over the four years. The emerging Internet of Nano-Things was found to be beneficial in many sectors
This document summarizes a research paper on using big data methodologies with IoT and its applications. It discusses how big data analytics is being used across various fields like engineering, data management, and more. It also discusses how IoT enables the collection of massive amounts of data from sensors and devices. Machine learning techniques are used to analyze this big data from IoT and enable communication between devices. The document provides examples of domains where big data and IoT are being applied, such as healthcare, energy, transportation, and others. It analyzes the similarities and differences in how big data techniques are used across these IoT domains.
Study on Issues in Managing and Protecting Data of IOTijsrd.com
This paper discusses variety of issues for preserving and managing data produced by IoT. Every second large amount of data are added or updated in the IoT databases across the heterogeneous environment. While managing the data each phase of data processing for IoT data is exigent like storing data, querying, indexing, transaction management and failure handling. We also refer to the problem of data integration and protection as data requires to be fit in single layout and travel securely as they arrive in the pool from diversified sources in different structure. Finally, we confer a standardized pathway to manage and to defend data in consistent manner.
This document discusses digital twin and big data towards smart manufacturing. It begins with an introduction on how new information technologies are enabling smart manufacturing through big data and digital twins. It then reviews the concepts of big data and digital twins in manufacturing, including their data sources and applications in product design, production planning, manufacturing and predictive maintenance. The document proceeds to compare big data and digital twins, discussing their similarities and differences from general and data perspectives. It concludes by discussing how big data and digital twins can be integrated to further promote smart manufacturing.
Insight into IoT Applications and Common Practice Challengesijtsrd
IoT caused a revolution in the technological world. Not only is the IoT related to computers, people or cell phones but also to various sensors, actuators, vehicles, and other modern appliances. There are around 14 billion interconnected digital devices across the globe i.e. almost 2 devices per human being on earth. The IoT serves as a medium to connect non living things to the internet to transfer information from one point to another in their community network which automates processes and ultimately makes the life of human beings convenient. The subsequent result of amalgamating internet connectivity with powerful data analysis is a complete change in the way we humans work and live. The most vital characteristics of IoT include connectivity, active engagement, sensors, artificial intelligence, and small device use. All of this creates many challenges that need to be solved to keep this technology to continue expanding. In this paper, we have identified various applications of IoT based on recent technological and business trends and highlighted the existing challenges faced by IoT which need to be addressed considering the exponential acceptance of the concept globally and the way those challenges had been addressed in the past. We have also made a few comments on the way such challenges are being attempted to be resolved now. This paper presents the current status Internet of Things IoT in terms of technical details, and applications. Also, this paper opens a window for future work on the historical approach to study and address IoT challenges. Lubna Alazzawi | Jamal Alotaibi "Insight into IoT Applications and Common Practice Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30286.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/30286/insight-into-iot-applications-and-common-practice-challenges/lubna-alazzawi
Secure Modern Healthcare System Based on Internet of Things and Secret Sharin...Eswar Publications
This document proposes an Internet of Things (IoT)-based system for healthcare and an authentication scheme to secure it. It first reviews existing literature on IoT and healthcare systems. It then presents the architecture of the proposed system, which has perception, network and application layers. Devices in the perception layer would collect health data from patients. The network layer would communicate this data to cloud servers via gateways. The application layer would manage devices, analyze data and share it with applications. The document proposes authenticating healthcare devices during access of patient data. It aims to enhance security in IoT-based healthcare through device authentication.
IRJET- Enabling Distributed Intelligence Assisted Future Internet of thing Co...IRJET Journal
This document proposes a new approach called the Future IoT Controller (FITC) that utilizes edge computing to provide distributed intelligence and low-latency insights for IoT applications. The FITC would be located at the network edge between IoT devices and the cloud to offer local intelligence through techniques like reinforcement learning. This would help reduce issues with cloud-based solutions like high latency, network loads, and inability to handle uncertain situations. The approach was tested in a simulated smart home environment and showed the feasibility of the FITC in providing faster responses, reducing rule complexity, and enabling predictions through learning from experiences at the edge.
FUTURE AND CHALLENGES OF INTERNET OF THINGS ijcsit
The document discusses the future challenges of the Internet of Things (IoT). It outlines technical challenges related to connectivity, compatibility, longevity, standards, security, and intelligent analysis. Business challenges involve investment and developing sustainable revenue models. Societal challenges include changing demands, new devices, costs, and ensuring customer trust. Legal challenges involve establishing laws, regulations, and policies around IoT. The document also discusses myths around IoT related to sensors, mobile data, data volume, data centers, interoperability standards, privacy, security, and limited vendors.
The world is moving forward at a fast pace, and the credit goes to ever growing technology. One such concept is IOT (Internet of things) with which automation is no longer a virtual reality. IOT connects various non-living objects through the internet and enables them to share information with their community network to automate processes for humans and makes their lives easier. The paper presents the future challenges of IoT , such as the technical (connectivity , compatibility and longevity , standards , intelligent analysis and actions , security), business ( investment , modest revenue model etc. ), societal (changing demands , new devices, expense, customer confidence etc. ) and legal challenges ( laws, regulations, procedures, policies etc. ). A section also discusses the various myths that might hamper the progress of IOT, security of data being the most critical factor of all. An optimistic approach to people in adopting the unfolding changes brought by IOT will also help in its growth.
This document summarizes a research paper on using big data methodologies with IoT and its applications. It discusses how big data analytics is being used across various fields like engineering, data management, and more. It also discusses how IoT enables the collection of massive amounts of data from sensors and devices. Machine learning techniques are used to analyze this big data from IoT and enable communication between devices. The document provides examples of domains where big data and IoT are being applied, such as healthcare, energy, transportation, and others. It analyzes the similarities and differences in how big data techniques are used across these IoT domains.
Study on Issues in Managing and Protecting Data of IOTijsrd.com
This paper discusses variety of issues for preserving and managing data produced by IoT. Every second large amount of data are added or updated in the IoT databases across the heterogeneous environment. While managing the data each phase of data processing for IoT data is exigent like storing data, querying, indexing, transaction management and failure handling. We also refer to the problem of data integration and protection as data requires to be fit in single layout and travel securely as they arrive in the pool from diversified sources in different structure. Finally, we confer a standardized pathway to manage and to defend data in consistent manner.
This document discusses digital twin and big data towards smart manufacturing. It begins with an introduction on how new information technologies are enabling smart manufacturing through big data and digital twins. It then reviews the concepts of big data and digital twins in manufacturing, including their data sources and applications in product design, production planning, manufacturing and predictive maintenance. The document proceeds to compare big data and digital twins, discussing their similarities and differences from general and data perspectives. It concludes by discussing how big data and digital twins can be integrated to further promote smart manufacturing.
Insight into IoT Applications and Common Practice Challengesijtsrd
IoT caused a revolution in the technological world. Not only is the IoT related to computers, people or cell phones but also to various sensors, actuators, vehicles, and other modern appliances. There are around 14 billion interconnected digital devices across the globe i.e. almost 2 devices per human being on earth. The IoT serves as a medium to connect non living things to the internet to transfer information from one point to another in their community network which automates processes and ultimately makes the life of human beings convenient. The subsequent result of amalgamating internet connectivity with powerful data analysis is a complete change in the way we humans work and live. The most vital characteristics of IoT include connectivity, active engagement, sensors, artificial intelligence, and small device use. All of this creates many challenges that need to be solved to keep this technology to continue expanding. In this paper, we have identified various applications of IoT based on recent technological and business trends and highlighted the existing challenges faced by IoT which need to be addressed considering the exponential acceptance of the concept globally and the way those challenges had been addressed in the past. We have also made a few comments on the way such challenges are being attempted to be resolved now. This paper presents the current status Internet of Things IoT in terms of technical details, and applications. Also, this paper opens a window for future work on the historical approach to study and address IoT challenges. Lubna Alazzawi | Jamal Alotaibi "Insight into IoT Applications and Common Practice Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-4 | Issue-3 , April 2020, URL: https://www.ijtsrd.com/papers/ijtsrd30286.pdf Paper Url :https://www.ijtsrd.com/engineering/computer-engineering/30286/insight-into-iot-applications-and-common-practice-challenges/lubna-alazzawi
Secure Modern Healthcare System Based on Internet of Things and Secret Sharin...Eswar Publications
This document proposes an Internet of Things (IoT)-based system for healthcare and an authentication scheme to secure it. It first reviews existing literature on IoT and healthcare systems. It then presents the architecture of the proposed system, which has perception, network and application layers. Devices in the perception layer would collect health data from patients. The network layer would communicate this data to cloud servers via gateways. The application layer would manage devices, analyze data and share it with applications. The document proposes authenticating healthcare devices during access of patient data. It aims to enhance security in IoT-based healthcare through device authentication.
IRJET- Enabling Distributed Intelligence Assisted Future Internet of thing Co...IRJET Journal
This document proposes a new approach called the Future IoT Controller (FITC) that utilizes edge computing to provide distributed intelligence and low-latency insights for IoT applications. The FITC would be located at the network edge between IoT devices and the cloud to offer local intelligence through techniques like reinforcement learning. This would help reduce issues with cloud-based solutions like high latency, network loads, and inability to handle uncertain situations. The approach was tested in a simulated smart home environment and showed the feasibility of the FITC in providing faster responses, reducing rule complexity, and enabling predictions through learning from experiences at the edge.
FUTURE AND CHALLENGES OF INTERNET OF THINGS ijcsit
The document discusses the future challenges of the Internet of Things (IoT). It outlines technical challenges related to connectivity, compatibility, longevity, standards, security, and intelligent analysis. Business challenges involve investment and developing sustainable revenue models. Societal challenges include changing demands, new devices, costs, and ensuring customer trust. Legal challenges involve establishing laws, regulations, and policies around IoT. The document also discusses myths around IoT related to sensors, mobile data, data volume, data centers, interoperability standards, privacy, security, and limited vendors.
The world is moving forward at a fast pace, and the credit goes to ever growing technology. One such concept is IOT (Internet of things) with which automation is no longer a virtual reality. IOT connects various non-living objects through the internet and enables them to share information with their community network to automate processes for humans and makes their lives easier. The paper presents the future challenges of IoT , such as the technical (connectivity , compatibility and longevity , standards , intelligent analysis and actions , security), business ( investment , modest revenue model etc. ), societal (changing demands , new devices, expense, customer confidence etc. ) and legal challenges ( laws, regulations, procedures, policies etc. ). A section also discusses the various myths that might hamper the progress of IOT, security of data being the most critical factor of all. An optimistic approach to people in adopting the unfolding changes brought by IOT will also help in its growth.
Internet of Things IoT Meaning, Application and Challengesijtsrd
The idea of making self- communicating devices conceived back in 1999 however it caught attention only after the British Entrepreneur Kevin Ashton christened the term Internet of Things. Since then, many distinguished researchers and other academicians of this domain have been adding significant knowledge on the fundamental concepts of IoT in the form of extensive researches, review papers and visual presentations. Here, in this paper, we are shedding light on the core concepts of Internet of Things. We further examine the potential impact of other existing or establishing technologies on IoT. We are presenting an extensive multi-facet report on the implementation of IoT while addressing many probable challenges that may occur in future. Ibrar Ahmed | Shilpi | Mohammad Amjad "Internet of Things (IoT) Meaning, Application and Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18773.pdf
A MIDDLEWARE FOR THE INTERNET OF THINGSIJCNCJournal
The Internet of Things (IoT) connects everyday objects including a vast array of sensors, actuators, and smart devices, referred to as “things” to the Internet, in an intelligent and pervasive fashion. This connectivity gives rise to the possibility of using the tracking capabilities of things to impinge on the location privacy of users. Most of the existing management and location privacy protection solutions do not consider the low-cost and low-power requirements of things; or, they do not account for the heterogeneity, scalability, or autonomy of communications supported in the IoT. Moreover, these traditional solutions do not consider the case where a user wishes to control the granularity of the disclosed information based on
the context of their use (e.g. based on the time or the current location of the user). To fill this gap, a middleware, referred to as the Internet of Things Management Platform (IoT-MP) is proposed in this paper.
Hardware/Software Interoperability and Single Point Vulnerability Problems of...BRNSS Publication Hub
As reiterated by many authors, internet of things (IoT) is the network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, actuators, and connectivity which enables these things to connect and exchange data, creating opportunities for more direct integration of the physical world into computer-based systems, resulting in efficiency improvements, economic benefits, and reduced human exertions. This is made possible by the communications models with the enabling technologies which make communications possible among IoT connected devices, although, with drawbacks. These drawbacks are the major reasons for adoption problems of IoT services by the society. This paper carried out an investigative study on previous works on the societal applications and adoption problems of IoT, IoT communications models, and pros and cons of IoT. Through the study, it was revealed that for IoT devices and services to be widely adopted with no or minimal problems, future IoT technology will not only address the known drawbacks but also will require hardware and software components that are highly interoperable, dependable, reconfigurable, and, in many applications, certifiable.
A Comprehensive Survey on Exiting Solution Approaches towards Security and Pr...IJECEIAES
‘Internet of Things (IoT)’emerged as an intelligent collaborative computation and communication between a set of objects capable of providing on-demand services to other objects anytime anywhere. A large-scale deployment of data-driven cloud applications as well as automated physical things such as embed electronics, software, sensors and network connectivity enables a joint ubiquitous and pervasive internet-based computing systems well capable of interacting with each other in an IoT. IoT, a well-known term and a growing trend in IT arena certainly bring a highly connected global network structure providing a lot of beneficial aspects to a user regarding business productivity, lifestyle improvement, government efficiency, etc. It also generates enormous heterogeneous and homogeneous data needed to be analyzed properly to get insight into valuable information. However, adoption of this new reality (i.e., IoT) by integrating it with the internet invites a certain challenges from security and privacy perspective. At present, a much effort has been put towards strengthening the security system in IoT still not yet found optimal solutions towards current security flaws. Therefore, the prime aim of this study is to investigate the qualitative aspects of the conventional security solution approaches in IoT. It also extracts some open research problems that could affect the future research track of IoT arena.
A Literature Review On Internet Of Things (IoT)April Smith
This document provides a literature review of research related to the Internet of Things (IoT) from a human-computer interaction (HCI) perspective. It analyzed 21 research papers on the topic, categorizing them into types and focuses of both research and commercial efforts. The review found that while HCI has engaged with technologies like ubiquitous and wearable computing that have IoT characteristics, the key difference is IoT's focus on interconnectivity between devices. It suggests HCI could further engage with IoT by ensuring a human-focused approach and considering how to address potential issues as the technology develops.
This document discusses hardware/software interoperability and single point vulnerability problems with internet of things (IoT) systems. It summarizes previous work that identified key barriers to wider IoT adoption, including a desire for components that are highly interoperable, dependable, reconfigurable, and certifiable. The document then examines IoT communication models like device-to-device, device-to-cloud, and device-to-gateway. While these models provide flexibility, interoperability challenges can arise from proprietary protocols and data formats. Future IoT systems will need to address these issues to gain broad societal acceptance.
The document discusses hardware/software interoperability and single point vulnerability problems with internet of things (IoT) systems. It provides background on IoT, describing how connected devices can communicate through different models including device-to-device, device-to-cloud, and device-to-gateway. The paper reviews literature on societal applications and adoption barriers for IoT. It finds that for widespread adoption, future IoT technologies will need highly interoperable and dependable hardware/software that is reconfigurable and certifiable to address known problems and vulnerabilities.
Application and Usefulness of Internet of Things in Information TechnologyDr. Amarjeet Singh
The Internet of Things (IoT) is a system of
interrelated computing devices, mechanical and digital
machines, objects, animals or people that are provided with
unique identifiers and the ability to transfer data over a
network without requiring human-to-human or human-tocomputer interaction. It is an ambiguous term, but it is fast
becoming a tangible technology that can be applied in data
centers to collect information on just about anything that
IT wants to control. IoT has evolved from the convergence
of wireless technologies, micro-electromechanical systems
(MEMS), microservices and the internet. The convergence
has helped tear down the silo walls between operational
technology (OT) and information technology (IT), allowing
unstructured machine-generated data to be analyzed for
insights that will drive improvements. The Internet of
Things (IoT) is essentially a system of machines or objects
outfitted with data-collecting technologies so that those
objects can communicate with one another. The machineto-machine (M2M) data that is generated has a wide range
of uses, but is commonly seen as a way to determine the
health and status of things -- inanimate or living.
IoT's rapid evolution marks the next stage in the innovation economy - White ...Technicolor
Like many new technology trends – such as Big Data or Cloud
Computing – that have captured the imagination of consumers
and business executives alike, the Internet of Things, or IoT,
has become a bit like a “Rorschach Test.” People see what they
want to see with the term is invoked.
To be fair, IoT lends itself to this tendency, because the concept
is so incredibly big, and its implications so deep. At its root IoT
is about devices talking to each other without human intervention
using the internet protocol. But this alone would cleanly fall into
the category of machine-to-machine (M2M) communications.
“When you look at what’s happening with IoT devices, explains
Danny Lousberg, Director of Product Management for Qeo
at Technicolor, “you will see a huge effort to create a vertical
ecosystem in which a specific device is communicating with a
specific back-end server that lives somewhere in the cloud to
tackle a specific use case for the user. And that means these
devices all are battling for a piece of mindshare and eyeballs.”
“The Internet of Things is inherently different from M2M
communication because M2M is really meant to solve large-scale
problems for a big group of devices that are all trying to work
together in a larger environment that is not necessarily controlled
by the end user.”
What makes IoT truly powerful is when M2M is linked to Mobility,
Big Data, Cloud Computing and other critical elements in today’s
modern technology infrastructure to empower and provide
options to end-users.
“From my perspectives, it will be virtually impossible to view these
technological paradigms independent of each other and from IoT,”
says Kurt Jonckheer, General Manager, Virdata, and VP, Strategic
Projects, Technicolor.
“The promise of IoT is that devices and appliances of all sorts
will, without human interference, interact with each other to
create a better experience for users by engaging in things like
self-diagnosis, harnessing event-driven actions that enhance
the human experience, or simply reduce costs in an intelligent
and automated manner.”
This combination of technologies is already generating billions
of dollars in revenue. Trillions more will be triggered as
businesses come to grips with the true potential of IoT.
Analyzing Role of Big Data and IoT in Smart CitiesIJAEMSJORNAL
Big data and Internet of Things (IoT) technologies have evolved and expanded tremendously and hence play a major role in building feasible initiatives for smart city development. IoT and big data form a perfect blend in bringing an interesting and novel challenge to attain futuristic smart cities. These new challenges mainly focus on business and technology related issues that help smart cities to formulate their principles, vision, & requirements of smart city applications. In this paper, the role of big data and IoT technologies with respect to smart cities is analyzed. The benefits that smart cities will have from big data and IoT are also discussed. Various challenges faced by smart cities in general related to big data and IoT have also been described here. Moreover, the future statistics of IoT and big data with respect to smart cities is also deliberated.
From Stand Alone Computers to Big Data Technology: Proposing a New Model for ...CrimsonpublishersMedical
Change is said to be constant but despite the benefits of change to Information Technology Infrastructure (ITI), managers, researchers and enthusiasts are uncertain about the future. A survey of literature shows that the association between ITI and change management are divergent in interrelationships. Many ITI consumers find it difficult to accommodate change due to several challenges involved. Technological developments coming into play has led to whole lot gradual changes. This paper describes the journey of ITI from standalone computers to cloud of things, the motivation for their transition alongside merits and demerits. It also discusses each of this method in brief and also provides their applications. It states the importance of computer networks today using fast and novel approaches. Finally, this paper presents a new model for managing change in ITI.
Efficient Data Filtering Algorithm for Big Data Technology in Telecommunicati...Onyebuchi nosiri
Efficient data filtering algorithm for Big Data technology Telecommunication is a concept aimed at effectively filtering desired information for preventive purposes, the challenges posed by unprecedented rise in volume, variety and velocity of information has necessitated the need for exploring various methods Big Data which is simply a data sets that are so large and complex that traditional data processing tools and technologies cannot cope with is been considered. The process of examining such data to uncover hidden patterns in them was evolved, this was achieved by coming up with an Algorithm comprising of various stages like Artificial neural Network, Backtracking Algorithm, Depth First Search, Branch and Bound and dynamic programming and error check. The algorithm developed gave rise to the flowchart, with each line of block representing a sub-algorithm.
Efficient Data Filtering Algorithm for Big Data Technology in Telecommunicati...Onyebuchi nosiri
This document summarizes an algorithm for efficiently filtering big data in telecommunications networks. It begins by introducing the challenges of unprecedented rises in data volume, variety, and velocity. It then describes an algorithm developed comprising stages like artificial neural networks and graph search methods. The algorithm is represented as a flowchart to filter data for preventative purposes like detecting criminal activity. Overall, the algorithm aims to effectively uncover patterns in large, complex datasets to help telecommunications providers address big data challenges.
Challenges and Opportunities of Internet of Things in Healthcare IJECEIAES
The Internet of Things (IoT) relies on physical objects interconnected between each other’s, creating a mesh of devices producing information and services. In this context, sensors and actuators are being continuously embedded in everyday objects (e.g., cars, home appliances, and smartphones) thus pervading our living environment. Among the plethora of application contexts, smart Healthcare is gaining momentum. Indeed IoT can revolutionize the healthcare industry by improving operational efficiency and clinical trials’ quality of monitoring, and by optimizing healthcare costs. This paper provides an overview of IoT, its applicability in healthcare, some insights about current trends and an outlook on future developments of healthcare systems.
This is a White Paper by Dave Evans, Cisco's Chief Futurist on the IoT, what it is and why it is important. I particularly the like the simple definition of IoT.
"The Internet of Things (IoT) - a definition - is simply the time when there are more objects connected to the Internet than people. this happened sometime in 2008/9."
This document provides an overview of the strategic research roadmap for the Internet of Things (IoT). It defines the IoT conceptual framework as a dynamic global network of physical and virtual "things" that are connected via standard communication protocols. The vision is for the IoT to merge with other internet developments to create a common global IT platform connecting people, things, energy networks, media, and services. Realizing this vision will require addressing challenges related to system architecture, management, business models, and ensuring security, privacy and interoperability as "things" become more connected and intelligent.
Study on Fog Computing and Data Concurrency in IoT. Includes an analysis of different data concurrency techniques, their principle and some recent developments in the area. Also covers the topic of Fog Computing and its development and application in IoT.
Novel authentication framework for securing communication in internet-of-things IJECEIAES
Internet-of-Things (IoT) offers a big boon towards a massive network of connected devices and is considered to offer coverage to an exponential number of the smart appliance in the very near future. Owing to the nascent stage of evolution of IoT, it is shrouded by security loopholes because of various reasons. Review of existing research-based solution highlights the usage of conventional cryptographic-based solution over the traditional mechanism of data forwarding process between IoT nodes and gateway. The proposed system presents a novel solution to this problem by a model that is capable of performing a highly secured and cost-effective authentication process. The proposed system introduces Authentication Using Signature (AUS) as well as Security with Complexity Reduction (SCR) for the purpose to resist participation of any form of unknown threats. The outcome of the model shows better security strength with faster response time and energy saving of the IoT nodes.
Internet of things iot based real time gas leakage monitoring and controllingIAEME Publication
This document summarizes a research paper that proposes using an Internet of Things (IoT) system to monitor for liquefied petroleum gas (LPG) leaks in real-time. The system would use sensors to detect leaks and send data over the internet using the Xively platform. If an emergency such as a gas leak or fire is detected, an alarm would sound and alerts would be sent to emergency responders. The real-time sensor data on Xively could then be used to determine when and where the emergency occurred to help identify the root cause. The goal is to develop a prototype for constant LPG leak monitoring with remote access to sensor data to enable quick emergency response.
Internet of Things IoT Meaning, Application and Challengesijtsrd
The idea of making self- communicating devices conceived back in 1999 however it caught attention only after the British Entrepreneur Kevin Ashton christened the term Internet of Things. Since then, many distinguished researchers and other academicians of this domain have been adding significant knowledge on the fundamental concepts of IoT in the form of extensive researches, review papers and visual presentations. Here, in this paper, we are shedding light on the core concepts of Internet of Things. We further examine the potential impact of other existing or establishing technologies on IoT. We are presenting an extensive multi-facet report on the implementation of IoT while addressing many probable challenges that may occur in future. Ibrar Ahmed | Shilpi | Mohammad Amjad "Internet of Things (IoT) Meaning, Application and Challenges" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-6 , October 2018, URL: http://www.ijtsrd.com/papers/ijtsrd18773.pdf
A MIDDLEWARE FOR THE INTERNET OF THINGSIJCNCJournal
The Internet of Things (IoT) connects everyday objects including a vast array of sensors, actuators, and smart devices, referred to as “things” to the Internet, in an intelligent and pervasive fashion. This connectivity gives rise to the possibility of using the tracking capabilities of things to impinge on the location privacy of users. Most of the existing management and location privacy protection solutions do not consider the low-cost and low-power requirements of things; or, they do not account for the heterogeneity, scalability, or autonomy of communications supported in the IoT. Moreover, these traditional solutions do not consider the case where a user wishes to control the granularity of the disclosed information based on
the context of their use (e.g. based on the time or the current location of the user). To fill this gap, a middleware, referred to as the Internet of Things Management Platform (IoT-MP) is proposed in this paper.
Hardware/Software Interoperability and Single Point Vulnerability Problems of...BRNSS Publication Hub
As reiterated by many authors, internet of things (IoT) is the network of physical devices, vehicles, home appliances, and other items embedded with electronics, software, sensors, actuators, and connectivity which enables these things to connect and exchange data, creating opportunities for more direct integration of the physical world into computer-based systems, resulting in efficiency improvements, economic benefits, and reduced human exertions. This is made possible by the communications models with the enabling technologies which make communications possible among IoT connected devices, although, with drawbacks. These drawbacks are the major reasons for adoption problems of IoT services by the society. This paper carried out an investigative study on previous works on the societal applications and adoption problems of IoT, IoT communications models, and pros and cons of IoT. Through the study, it was revealed that for IoT devices and services to be widely adopted with no or minimal problems, future IoT technology will not only address the known drawbacks but also will require hardware and software components that are highly interoperable, dependable, reconfigurable, and, in many applications, certifiable.
A Comprehensive Survey on Exiting Solution Approaches towards Security and Pr...IJECEIAES
‘Internet of Things (IoT)’emerged as an intelligent collaborative computation and communication between a set of objects capable of providing on-demand services to other objects anytime anywhere. A large-scale deployment of data-driven cloud applications as well as automated physical things such as embed electronics, software, sensors and network connectivity enables a joint ubiquitous and pervasive internet-based computing systems well capable of interacting with each other in an IoT. IoT, a well-known term and a growing trend in IT arena certainly bring a highly connected global network structure providing a lot of beneficial aspects to a user regarding business productivity, lifestyle improvement, government efficiency, etc. It also generates enormous heterogeneous and homogeneous data needed to be analyzed properly to get insight into valuable information. However, adoption of this new reality (i.e., IoT) by integrating it with the internet invites a certain challenges from security and privacy perspective. At present, a much effort has been put towards strengthening the security system in IoT still not yet found optimal solutions towards current security flaws. Therefore, the prime aim of this study is to investigate the qualitative aspects of the conventional security solution approaches in IoT. It also extracts some open research problems that could affect the future research track of IoT arena.
A Literature Review On Internet Of Things (IoT)April Smith
This document provides a literature review of research related to the Internet of Things (IoT) from a human-computer interaction (HCI) perspective. It analyzed 21 research papers on the topic, categorizing them into types and focuses of both research and commercial efforts. The review found that while HCI has engaged with technologies like ubiquitous and wearable computing that have IoT characteristics, the key difference is IoT's focus on interconnectivity between devices. It suggests HCI could further engage with IoT by ensuring a human-focused approach and considering how to address potential issues as the technology develops.
This document discusses hardware/software interoperability and single point vulnerability problems with internet of things (IoT) systems. It summarizes previous work that identified key barriers to wider IoT adoption, including a desire for components that are highly interoperable, dependable, reconfigurable, and certifiable. The document then examines IoT communication models like device-to-device, device-to-cloud, and device-to-gateway. While these models provide flexibility, interoperability challenges can arise from proprietary protocols and data formats. Future IoT systems will need to address these issues to gain broad societal acceptance.
The document discusses hardware/software interoperability and single point vulnerability problems with internet of things (IoT) systems. It provides background on IoT, describing how connected devices can communicate through different models including device-to-device, device-to-cloud, and device-to-gateway. The paper reviews literature on societal applications and adoption barriers for IoT. It finds that for widespread adoption, future IoT technologies will need highly interoperable and dependable hardware/software that is reconfigurable and certifiable to address known problems and vulnerabilities.
Application and Usefulness of Internet of Things in Information TechnologyDr. Amarjeet Singh
The Internet of Things (IoT) is a system of
interrelated computing devices, mechanical and digital
machines, objects, animals or people that are provided with
unique identifiers and the ability to transfer data over a
network without requiring human-to-human or human-tocomputer interaction. It is an ambiguous term, but it is fast
becoming a tangible technology that can be applied in data
centers to collect information on just about anything that
IT wants to control. IoT has evolved from the convergence
of wireless technologies, micro-electromechanical systems
(MEMS), microservices and the internet. The convergence
has helped tear down the silo walls between operational
technology (OT) and information technology (IT), allowing
unstructured machine-generated data to be analyzed for
insights that will drive improvements. The Internet of
Things (IoT) is essentially a system of machines or objects
outfitted with data-collecting technologies so that those
objects can communicate with one another. The machineto-machine (M2M) data that is generated has a wide range
of uses, but is commonly seen as a way to determine the
health and status of things -- inanimate or living.
IoT's rapid evolution marks the next stage in the innovation economy - White ...Technicolor
Like many new technology trends – such as Big Data or Cloud
Computing – that have captured the imagination of consumers
and business executives alike, the Internet of Things, or IoT,
has become a bit like a “Rorschach Test.” People see what they
want to see with the term is invoked.
To be fair, IoT lends itself to this tendency, because the concept
is so incredibly big, and its implications so deep. At its root IoT
is about devices talking to each other without human intervention
using the internet protocol. But this alone would cleanly fall into
the category of machine-to-machine (M2M) communications.
“When you look at what’s happening with IoT devices, explains
Danny Lousberg, Director of Product Management for Qeo
at Technicolor, “you will see a huge effort to create a vertical
ecosystem in which a specific device is communicating with a
specific back-end server that lives somewhere in the cloud to
tackle a specific use case for the user. And that means these
devices all are battling for a piece of mindshare and eyeballs.”
“The Internet of Things is inherently different from M2M
communication because M2M is really meant to solve large-scale
problems for a big group of devices that are all trying to work
together in a larger environment that is not necessarily controlled
by the end user.”
What makes IoT truly powerful is when M2M is linked to Mobility,
Big Data, Cloud Computing and other critical elements in today’s
modern technology infrastructure to empower and provide
options to end-users.
“From my perspectives, it will be virtually impossible to view these
technological paradigms independent of each other and from IoT,”
says Kurt Jonckheer, General Manager, Virdata, and VP, Strategic
Projects, Technicolor.
“The promise of IoT is that devices and appliances of all sorts
will, without human interference, interact with each other to
create a better experience for users by engaging in things like
self-diagnosis, harnessing event-driven actions that enhance
the human experience, or simply reduce costs in an intelligent
and automated manner.”
This combination of technologies is already generating billions
of dollars in revenue. Trillions more will be triggered as
businesses come to grips with the true potential of IoT.
Analyzing Role of Big Data and IoT in Smart CitiesIJAEMSJORNAL
Big data and Internet of Things (IoT) technologies have evolved and expanded tremendously and hence play a major role in building feasible initiatives for smart city development. IoT and big data form a perfect blend in bringing an interesting and novel challenge to attain futuristic smart cities. These new challenges mainly focus on business and technology related issues that help smart cities to formulate their principles, vision, & requirements of smart city applications. In this paper, the role of big data and IoT technologies with respect to smart cities is analyzed. The benefits that smart cities will have from big data and IoT are also discussed. Various challenges faced by smart cities in general related to big data and IoT have also been described here. Moreover, the future statistics of IoT and big data with respect to smart cities is also deliberated.
From Stand Alone Computers to Big Data Technology: Proposing a New Model for ...CrimsonpublishersMedical
Change is said to be constant but despite the benefits of change to Information Technology Infrastructure (ITI), managers, researchers and enthusiasts are uncertain about the future. A survey of literature shows that the association between ITI and change management are divergent in interrelationships. Many ITI consumers find it difficult to accommodate change due to several challenges involved. Technological developments coming into play has led to whole lot gradual changes. This paper describes the journey of ITI from standalone computers to cloud of things, the motivation for their transition alongside merits and demerits. It also discusses each of this method in brief and also provides their applications. It states the importance of computer networks today using fast and novel approaches. Finally, this paper presents a new model for managing change in ITI.
Efficient Data Filtering Algorithm for Big Data Technology in Telecommunicati...Onyebuchi nosiri
Efficient data filtering algorithm for Big Data technology Telecommunication is a concept aimed at effectively filtering desired information for preventive purposes, the challenges posed by unprecedented rise in volume, variety and velocity of information has necessitated the need for exploring various methods Big Data which is simply a data sets that are so large and complex that traditional data processing tools and technologies cannot cope with is been considered. The process of examining such data to uncover hidden patterns in them was evolved, this was achieved by coming up with an Algorithm comprising of various stages like Artificial neural Network, Backtracking Algorithm, Depth First Search, Branch and Bound and dynamic programming and error check. The algorithm developed gave rise to the flowchart, with each line of block representing a sub-algorithm.
Efficient Data Filtering Algorithm for Big Data Technology in Telecommunicati...Onyebuchi nosiri
This document summarizes an algorithm for efficiently filtering big data in telecommunications networks. It begins by introducing the challenges of unprecedented rises in data volume, variety, and velocity. It then describes an algorithm developed comprising stages like artificial neural networks and graph search methods. The algorithm is represented as a flowchart to filter data for preventative purposes like detecting criminal activity. Overall, the algorithm aims to effectively uncover patterns in large, complex datasets to help telecommunications providers address big data challenges.
Challenges and Opportunities of Internet of Things in Healthcare IJECEIAES
The Internet of Things (IoT) relies on physical objects interconnected between each other’s, creating a mesh of devices producing information and services. In this context, sensors and actuators are being continuously embedded in everyday objects (e.g., cars, home appliances, and smartphones) thus pervading our living environment. Among the plethora of application contexts, smart Healthcare is gaining momentum. Indeed IoT can revolutionize the healthcare industry by improving operational efficiency and clinical trials’ quality of monitoring, and by optimizing healthcare costs. This paper provides an overview of IoT, its applicability in healthcare, some insights about current trends and an outlook on future developments of healthcare systems.
This is a White Paper by Dave Evans, Cisco's Chief Futurist on the IoT, what it is and why it is important. I particularly the like the simple definition of IoT.
"The Internet of Things (IoT) - a definition - is simply the time when there are more objects connected to the Internet than people. this happened sometime in 2008/9."
This document provides an overview of the strategic research roadmap for the Internet of Things (IoT). It defines the IoT conceptual framework as a dynamic global network of physical and virtual "things" that are connected via standard communication protocols. The vision is for the IoT to merge with other internet developments to create a common global IT platform connecting people, things, energy networks, media, and services. Realizing this vision will require addressing challenges related to system architecture, management, business models, and ensuring security, privacy and interoperability as "things" become more connected and intelligent.
Study on Fog Computing and Data Concurrency in IoT. Includes an analysis of different data concurrency techniques, their principle and some recent developments in the area. Also covers the topic of Fog Computing and its development and application in IoT.
Novel authentication framework for securing communication in internet-of-things IJECEIAES
Internet-of-Things (IoT) offers a big boon towards a massive network of connected devices and is considered to offer coverage to an exponential number of the smart appliance in the very near future. Owing to the nascent stage of evolution of IoT, it is shrouded by security loopholes because of various reasons. Review of existing research-based solution highlights the usage of conventional cryptographic-based solution over the traditional mechanism of data forwarding process between IoT nodes and gateway. The proposed system presents a novel solution to this problem by a model that is capable of performing a highly secured and cost-effective authentication process. The proposed system introduces Authentication Using Signature (AUS) as well as Security with Complexity Reduction (SCR) for the purpose to resist participation of any form of unknown threats. The outcome of the model shows better security strength with faster response time and energy saving of the IoT nodes.
Internet of things iot based real time gas leakage monitoring and controllingIAEME Publication
This document summarizes a research paper that proposes using an Internet of Things (IoT) system to monitor for liquefied petroleum gas (LPG) leaks in real-time. The system would use sensors to detect leaks and send data over the internet using the Xively platform. If an emergency such as a gas leak or fire is detected, an alarm would sound and alerts would be sent to emergency responders. The real-time sensor data on Xively could then be used to determine when and where the emergency occurred to help identify the root cause. The goal is to develop a prototype for constant LPG leak monitoring with remote access to sensor data to enable quick emergency response.
Similar to The Dynamics of the Ubiquitous Internet of Things (IoT) and Trailblazing Data Mining (DM) (20)
How to Download & Install Module From the Odoo App Store in Odoo 17Celine George
Custom modules offer the flexibility to extend Odoo's capabilities, address unique requirements, and optimize workflows to align seamlessly with your organization's processes. By leveraging custom modules, businesses can unlock greater efficiency, productivity, and innovation, empowering them to stay competitive in today's dynamic market landscape. In this tutorial, we'll guide you step by step on how to easily download and install modules from the Odoo App Store.
Creative Restart 2024: Mike Martin - Finding a way around “no”Taste
Ideas that are good for business and good for the world that we live in, are what I’m passionate about.
Some ideas take a year to make, some take 8 years. I want to share two projects that best illustrate this and why it is never good to stop at “no”.
Brand Guideline of Bashundhara A4 Paper - 2024khabri85
It outlines the basic identity elements such as symbol, logotype, colors, and typefaces. It provides examples of applying the identity to materials like letterhead, business cards, reports, folders, and websites.
How to Manage Reception Report in Odoo 17Celine George
A business may deal with both sales and purchases occasionally. They buy things from vendors and then sell them to their customers. Such dealings can be confusing at times. Because multiple clients may inquire about the same product at the same time, after purchasing those products, customers must be assigned to them. Odoo has a tool called Reception Report that can be used to complete this assignment. By enabling this, a reception report comes automatically after confirming a receipt, from which we can assign products to orders.
The Dynamics of the Ubiquitous Internet of Things (IoT) and Trailblazing Data Mining (DM)
1. International Journal of Wireless & Mobile Networks (IJWMN), Vol.14, No.3, June 2022
DOI:10.5121/ijwmn.2022.14302 21
THE DYNAMICS OF THE UBIQUITOUS
INTERNET OF THINGS (IOT) AND
TRAILBLAZING DATA MINING (DM)
Bongs Lainjo
Cybermatic International, Canada
ABSTRACT
The research study intends to understand the thematic dynamics of the internet of things (IoT), thereby
aiming to address the general objective i.e. “To explore and streamline the IoT thematic dynamics with a
focus on cross-cutting data mining, and IoT apps evidence-based publication trends”. To meet this
objective, secondary research has been compiled as part of the analytic process. It was found from the
research that IoT continues to evolve with significant degrees of proliferation. Complementary and
trailblazing data mining (DM) with more access to cloud computing platforms has catalyzed accelerating
the achievement of planned technological innovations. The outcome has been myriads of apps currently
used in different thematic landscapes. Based on available data on app searches by users, and between
2016 and 2019, themes like sports, supply chain, and agriculture maintained positive trends over the four
years. The emerging Internet of Nano-Things was found to be beneficial in many sectors. Wireless Sensor
Networks (WSNs) were also found to be emerging with more accurate and effective results in gathering
information along with processing data and communication technologies.
In summary, available data indicate that IoT is happening and has a significant implication on data
mining. All indications suggest that it will continue to grow and increasingly affect how we interact with
“things”. A backdrop of concerns exists ranging from developing standard protocols to protecting
individual privacy.
KEYWORDS
IoT, Data Mining (DM), Trail Blaze, Ubiquitous, Evolution
1. INTRODUCTION
Over time, information technology has evolved and transformed our daily way of living. The past
three decades have witnessed an unprecedented evolution of high technology and its associated
themes. Everyone can attest that their life quality has improved thanks to the incorporation of
technology in various sectors such as business and it has increased people’s motivation towards
getting the best results possible. In general, there is very little doubt that technological
innovations have served as an impetus behind these dynamics. The Internet of Things (IoT) has
served and continues to demonstrate the usefulness of human-machine integration through
sensors, and the transformation and manipulation of data through different data mining platforms.
It was the increase in communication protocol development, network creations, and increased
focus on Artificial Intelligence that birthed the IoT. According to Kong [1], the IoT involves the
information of physical objects, including sensors, machines, cars, buildings, and other items,
that allow interaction and cooperation of these objects for achieving specific goals. Others, such
as Welbourne et al. [2], provided more detailed descriptions. That is, IoT was presented as a
structure of computing that facilitates data transfer between digital and mechanical appliances
2. International Journal of Wireless & Mobile Networks (IJWMN), Vol.14, No.3, June 2022
22
without involving human interaction. This makes it capable of data mining. For example,
Hancock and Hancock [3] mentioned that IoT has three important ramifications including data
collection, remote control capability, and communication between objects. Data cannot be useful
when it stands alone since it is vital to have ways for transforming the data into useful
information. In this regard, a literature review conducted by Chen et al. [4] observed that
algorithms could be applied to IoT for extracting meaningful data. Consequently, the practice of
identifying data patterns that are useful from huge datasets and utilizing for patterns or hidden
information extraction is referred to as data mining (DM). DM can also be perceived as the
exploration and transformation of data that ultimately generates information, which reveals
historically undiscovered trends and patterns. These dynamics are useful in making informed
decisions or predictions in significant cases.
In this paper, DM is specifically highlighted as an indication of its importance and cross-cutting
role in data analytics. Its invaluable contribution in propagating the transformations involved with
different IoT themes cannot be adequately emphasized. The logical layout of the article includes
background, settings, thematic proliferation, thematic implications, prognoses, and more.
2. BACKGROUND
IoT and data mining are complementary platforms. These two technologies have also had a
longstanding effect on various thematic areas including the development of IoT-enabled
technologies such as sensors for data collection, IoT-based systems of communication and data
transfer, and similar kinds of technologies [5]. The IoT and its impact on data mining have rich
backgrounds beginning with the onset of the internet. This has been highlighted in the studies of
Xia et al. [6] and WuHe et al. [5]. Some concerns associated with these platforms include
security, future developments : future architectures, regulations, and standardizations.
The IoT refers to a variety of things that are typically connected to the Internet to enhance the
sharing of data with other things. IoT-connected machines and devices can improve how human
beings work and live. An article by Kim et al. [7] suggested that IoT and its applicable
technologies can integrate classical networks. Consequently, IoT has been serving a vital purpose
ever since it appeared, contributing to innovative applications ranging from traditional equipment
to general house hold devices. It has been attracting the researchers' attention from industry,
government, and academia in the past years. The recent introduction of various transformative
technology into IoT such as data mining have helped it to become more effective [8].
An article by Bin et al. [9] suggested that data mining entails discovering novel, potentially
exciting patterns, particularly from large relevant data sets : data dredging and data archeology.
The main aim of any data mining is to build an efficient descriptive or predictive model using a
vast amount of the most appropriate and relevant data. There are various implications of IoT in
data mining. Some are explained in the following paragraphs.
Firstly, an article by Dachyar et al. [10] mentioned that the term IoT first emerged in a published
paper in the year 2006, showing the paradigm of the evolving concept of internet technology. The
concept of IoT is very crucial in con temporary circumstances [11]. They further added that the
technologies that both shape and support IoT have been in evolution for several years. In the
study conducted by Chen et al. [4], data-center architectures are significantly growing and are
found to be more distributed to accommodate the data that IoT is generating. The distributed
strategy to edge computing is mainly designed to meet the real-time processing requirements
needed for new IoT applications in the field [12]. Most business operations have extended their
data centers to the public cloud to process, assess, and store vast volumes of IoT data.
3. International Journal of Wireless & Mobile Networks (IJWMN), Vol.14, No.3, June 2022
23
In an article by Cai et al. [13], the researchers reveal that IoT devices, sensors, and machines
generate a vast amount of data every second. It has further been found that cloud computing
assists in both the storage and analysis of the data. This enables the enterprise to get the
maximum gains of an IoT infrastructure [14]. Hence, the IoT solution connects people, things,
and processes, while cloud computing plays a crucial role in this collaboration to enhance high
visibility.
In a study conducted by Shi et al. [15], with the assistance of edge computing, intelligence in data
mining moves to the edge. There are various scenarios where high-speed data is the key
component of analytics, which assists in processing data with edge computing [16]. The critical
cases of IoT for edge computing include security concerns and the evolution of cloud computing.
According to Ren et al. [17], trail blazers ranked trust issues as one of the significant concerns,
ahead of technology issues. Besides, there are frequently two or three times the likelihood of
more laggards to address privacy issues, data integrity, and cyber security, including other
dimensions of trusted technology. For instance, trail blazers are probably more likely to think of
matters concerning security at the start of the IoT initiatives or choose private networks that play
a crucial role by limiting threat pressure [18].
IoT results in a massive amount of data. Literature reveals that this might possess some prognosis
in the field of e-commerce [19]. First, making information and data available to people enhances
government transparency. Transparency helps in ensuring proper insight and also reduces
government waste. A good way that the enormous data gathered by IoT helps consumers and
businesses is through empowering them towards better decision-making [20]. The IoT further
gives users knowledgeable advice.
Firms are significantly turning to IoT as their sources of data because these are typically derived
from regular monitoring of a vast range of things with in different situations, which become
available. In a study conducted by Misuraca [21], the IoT brings with it new business ventures.
The risks such as the lack of well-coordinated policies and regulations about IoT can significantly
impede its application and implementation [22]. As a result, organizations should, therefore,
develop policies and regulations and also consider their role in enabling the development of IoT
very carefully. Any IoT corporation should demonstrate an inevitable out break growth to
enhance developments [23].
In a study conducted by Saidu et al. [24], the authors indicate that the advent of the Internet has
played a crucial role in information technology and has resulted in more effective modes of
communication. Handheld devices, such as mobile phones, have made access to ambiguous
information processing more feasible [25]. IoT has made it easier for most commercial operations
as they can keep in touch with their clients.
The scope of IoT remains quite wide. If the number of peer-reviewed publications is any
indication, the challenges and degree of IoT technological innovations continue to expand
unabated at an alarming rate. As the adage goes, necessity is the mother of invention. IoT is no
exception as confirmed by the abundant and growing number of related themes associated with
IoT. An extensive and analytic perspective is presented else where in the paper.
Lastly, IoT is changing the gravitational constant in our technological world. As it matures, the
black holes of data gravity in which clouds have been placed will eventually be ripped part from
the millions of smaller data planets [25]. The smaller planets will be situated in houses, factories,
buildings, or any where else where the IoT runs to make the data actionable. Thus, we have to
4. International Journal of Wireless & Mobile Networks (IJWMN), Vol.14, No.3, June 2022
24
keep all our applications blazing fast by running them at a hundred percent. In addition, we can
not leave all our applications vulnerable to the so-called nature of the Internet.
3. SETTINGS
Jacob Morgan supposed that anything that can be connected would be connected [3]. Morgan
referred to the future concerning IoT as an assertion based on an informed observation of the
trend in the IoT space. For instance, according to Kong et al. [1], various countries have adopted
strategies based on the rapid development of IoT technologies with good examples being China
with its Made-in-China 2025 strategy, the US through its American Advanced Manufacturing
Partnership Program, and Germany’s German Industry 4.0 strategy. In light of these strategies
accordingly, the IoT will continue to influence significant paradigm shifts, especially in data
management and applications. Notably, Liu et al. [26] underlined that IoT devices collect high
quality data that is utilized in new technological developments (see Figure 1). Some of these
areas include IoT data mining and analytics, development of Sensors for data collection and
management, e-health, and Big Data analytics.
Figure 1. IoT Ecosystem Platform (Source: Author)a
4. THEMATIC PROLIFERATION OF IOT
During the period July 21 and 24, 2020, a four-year retrospective (2016 -2019) database was
compiled through searches using the Goggle Scholar framework. The selection of the four years
was influenced by accessibility to recent datasets. Besides, having a minimum number of points
was also vital for facilitating possible trends’ identification (see Figures 2 and 3).
In general, there were 103 themes. Among these and based on four-year means, the theme with
the highest number of publications was the “resource management and access control” theme
with 374000 publications. At the bottom, the theme with the least number of publications was
“new human-device interaction with two publications”.
The annual median publications for all the themes over four years were 5415, 8930, 11400, and
11700 for 2016, 2017, 2018, and 2019 respectively. The averages are not reported here because
of their insensitivity to extreme values, which were quite prevalent in the data set. The annual
5. International Journal of Wireless & Mobile Networks (IJWMN), Vol.14, No.3, June 2022
25
trends were as follows: Between 2016 and 2017, most (88 percent) of the themes had an increase
in the number of publications. Between 2017 and 2018, 81 percent of themes had a positive
change in the number of publications. And finally, from 2018 to 2019, the increase rate was 79
percent.
4.1. Select Themes
The reason for including the select themes in the detailed analysis was that the general population
readership could resonate and recognize them. They include healthcare, education, engineering,
household, transportation agriculture research, law enforcement, security and Trust, business,
manufacturing, supply chains, resource management, location, smart cities, and social media.
The four-year average (Figure 1) position “Resource Management” at the top with 374250
publications, followed by “Social Models “with 251000 publications. The bottom two themes
were “household” and “supply chain” with 2420 and 1398 publications respectively.
Highlights of the selected themes are also included to explore further a more complementary
perspective of these themes. Among these 18 themes (Figure 2), the number of publications in 22
percent had an annual decline in four years; seventeen percent declined on the fourth year only
with “smart city” the only theme with two consecutive declines during the last two years. The rest
had an increasing number of publications over that time frame. Concerning inching trends,
“supply chains” increased the most (102 percent) between 2016 and 2017; 50 percent between
2017 and 2018, and 56 percent between 2018 and 2019. On the other side of the spectrum,
“localization technologies” had a downward trend of 26 percent between 2016 and 2017, 41
percent and 18 percent fall in the number of publications between 2018 and 2019 with the
“resource management” dropping 41 percent in its number of publications between 2017 and
2018. There was not a single theme with the trend change of annual publications higher than the
preceding year.
In summary, these dynamics suggest the extent to which IoT technological innovations can serve
as a proxy to the number of IoT thematic publications. There is also the likelihood that these
innovations can be used to predict ongoing research themes. The implications range from
thematic knowledge sharing to exponential research challenges.
Figure 2. 4-year Averages of Select IoT Themes (Data Source: Google Scholar, Author)
6. International Journal of Wireless & Mobile Networks (IJWMN), Vol.14, No.3, June 2022
26
Figure 3. Select IoT Thematic Trends - 2016-2019 (Data Source: Google Scholar, Author)
4.2. The Matic Implications
Concerning the research topic i.e. IoT and DM, several implications have been identified in the
existing literature. Deloitte [27], in its report, underlined information system platforms’ influence
in the development of a huge scope for future improvements through its effects on the current
dynamics. For instance, IoT cloud platforms are becoming increasingly important in the global
market. Hence, the IoT cloud platform market was worth 6.4 billion USD in the year 2020. With
this, the IoT solution segment has been significantly dominated by the IoT monetization market.
Hence, due to this reason, it has been estimated that the cloud platform market has an immense
scope in its future growth, thereby generating about 11.5 billion USD by the year 2025. This
further infers that the trend will continue in the future because more organizations have started to
adopt these solutions [27].
Considering the potential of IoT to avail intelligent platforms, Hassan [28] stated that it has a
significant scope of providing intelligent platforms to facilitate the collaboration of distributed
objects through wired networks or local-area wireless networks. Furthermore, information system
platforms have been specifically integrated by healthcare organizations through IoT health
monitoring systems. These platforms offer an effective environment of intelligence for assisting
and monitoring patients in remote areas. Specifically, these devices are used by IoT systems for
ensuring that they can be controlled and queried by other platforms, applications, and controllers.
This further coordinates with multiple objects without the human users’ interference. Even in the
aquarium environment, such kinds of platforms have been used, such as in the case of Libelium.
This platform used sensors that monitored several aspects of water and utilized actuators along
with pump devices that regulated and administered medicines. Most importantly, it was
7. International Journal of Wireless & Mobile Networks (IJWMN), Vol.14, No.3, June 2022
27
responsible for sending wireless information, which is gathered by the sensors. Additionally,
actions are initiated by the actuators to the mobile interface or web interface accordingly [28].
Gubbi et al. [29] affirmed that cloud computing provided an appropriate platform, which acts as a
receiver of data from ubiquitous sensors. It also played the role of a computer that interpreted, as
well as analyzed the data along with availing the users with web-based visualization, which
becomes easy to understand. Besides, to develop ubiquitous healthcare, IoT has been providing
proper platforms so that body area sensors can be used for uploading the data to the servers [29].
However, Elkhodr et al. [30] argued that IoT incorporation needs proper standards for enabling
horizontal platforms, which are programmable, communicable, and operable across devices
irrespective of their model or industry applications. It was also observed that several studies
reported privacy issues while using mobile applications on relevant phone platforms. Therefore,
it has been suggested “it is most likely that privacy incidents will grow rapidly with the increase
in penetration of the IoT in our daily life. Thus, privacy remains a major problem as IoT
develops. When it comes to IoT, anonymity does not count as privacy. IoTs are designed to
automatically collect data, store them, and easily share and analyse personal data, which can have
potential adverse effects on individuals.”[30].
Another prominent platform, which that has been taken into consideration in Figure 1 is the data
mining algorithm. In this context, Sunhare et al. [31] asserted that if a proper data mining
algorithm is processed with different types of data, then valuable knowledge can be gathered.
Nevertheless, a challenging aspect evident in such instances is that it is difficult to synthesize or
select the most feasible data mining algorithm. Chen et al. ([4] further stated that these kinds of
algorithms can be efficiently used to gather private or hidden information from the available data.
It has also highlighted that more devices are being connected to IoT and hence, a large amount of
data must be analyzed. Furthermore, the latest algorithms must be modified for applying them to
big data. It also estimates that big data-related mining systems will be most appropriate to be
developed in the future for obtaining better results. Specifically, it has been noted in this study
that data mining involves the application of algorithms to the gathered data for finding patterns
and evaluating the same related to discovered knowledge [4]. Data compilation is another
important platform associated with IoT, which is essential in the concerned environment, wherein
the issue of data compression, storage, analysis, and visualization were duly addressed with the
help of data curation of IoT sensor data in the cloud platform. It has also been found that for
edge-based machine learning, as well as energy-efficient data, a compression approach was
suggested in terms of IoT [32]. Besides, Brous et al. [33] found out that informed system rollout
and informed decision-making are also involved in the IoT ecosystem platform. This is because
the IoT has been adopted for reconfiguring the processes of decision-making, especially in asset
management. Furthermore, there is the future scope of better utilization as well. Hence, it has
been suggested that it is important to gather the right information for attaining the best outcomes
[33].
4.3. Prognoses
In a statement by Hancock and Hancock [3], authors indicate that it is hard to know the size or
state of the IoT because it is evolving so rapidly. A similar opinion is observed by Kong, et al. [1]
where an increase in data mining and consequent demand for data storage is predicted. It has
been understood that in the future, the IoT technologies will better integrate with the internet for
developing accurate solutions to interchange and communicate information through sensing
devices. It has been estimated that in the future, wider technological trends will be evidenced
through the enablers such as manufacturing, energy, communication, standards, integration,
intelligence, and interoperability. Additionally, RFID technology will be considered mainstream
8. International Journal of Wireless & Mobile Networks (IJWMN), Vol.14, No.3, June 2022
28
in the retail sector. Besides, ambient intelligence will be mastered alongside interacting virtual
world with that of the physical one [34].
Hussein [35] asserted that “Owing to the fact that IoT has become a vital element as regards the
future of the internet with its increased usage, it necessitates a need to adequately address security
and trust functions” (p. 80). It has been further understood that IoT along with DM has several
future applications and a scope of improvement. In the future, IoT can be applied to develop
smart cities, which would require using sensors and radio frequency identification. The
application of the Internet of Nano-things (IoNT) can also be explored in the field of healthcare,
which will enable organizations to collect new medical data. It will further be responsible for
conducting better diagnoses and discoveries (see Figure 4). Smart agriculture, as well as water
management, can also be done by implementing IoT and DM in the future. The IoT ecosystem
platforms can also be used in the logistics and retail sector, which will contribute to improving
the small living standards of the citizens. Additionally, IoT can also be explored in collaboration
with blockchain technology in the future for enhancing overall security and privacy or security
issues [35]. It has also been understood that IoT will explore all kinds of application areas in near
future. These areas also involve big data analytics, which enables organizations to undertake
accurate decisions for developing enhanced IoT systems [36].
Figure 4. Internet of Nano-Things. (Source: Hussein, 2019)
5. THE FUTURE OF TECHNOLOGY
The preceding literature has presented IoT and its implication on data mining as rapidly growing
[3], [4]. Some have described it as ever-growing, while others have illustrated its future as hard to
quantify due to available possibilities for growth [3]. For instance, when Jacob Morgan mentions
that eventually “anything that can be connected will be connected”, it signifies that the
implication of IoT on data mining will be significant. For instance, even Kong, et al. [1],
mentioned that with the increase in IoT business, the demand for data storage and computing will
put pressure on the ability of cloud computing. In this regard, data mining’s scope in the future
must also be explored. Hence, it was estimated by Venkatadri and Reddy [37] that data mining
also has a vast scope in the upcoming days. This is because soft computing approaches can be
explored, for instance, genetic programming, fuzzy logic, and neural networks. These kinds of
techniques can be incorporated with the help of cloud computing and multi-agent technologies.
The prime areas, wherein these technological advancements can be applied involve medical
diagnosis, business, social networking, research and scientific analysis, and the web [37]. Apart
from these areas, healthcare applications can also be highly estimated. This is because “IoT in
9. International Journal of Wireless & Mobile Networks (IJWMN), Vol.14, No.3, June 2022
29
healthcare has the potential to make a reality that All staff in hospital areas can benefit from
access to an up-to-date electronic health record detailing the patient’s condition and treatment,
and affording access to their information, medical history, services and diagnostics” (p. 4). The
power of DM has also been identified in this study, wherein it has been found that “Recent AI
technology allows to expand the fields of Data Mining as well as the speed under the new
evolution of storage and processing performances of computing machines” [37].
5.1. Findings
There are considerable implications of IoT on data mining. Some of the already experienced
effects include increased efficiency in data capture and processing, more accurate statistics,
facilitation of collection and transfer of big data, among other implications [5], [26]. The paper
also finds potential challenges including data security and impact on privacy through IoT-enabled
data mining. Additionally, Deloitte [27] asserted that IoT platforms such as IoT orchestration,
which is a single platform, have been offering organizations the ability to integrate the existing
systems and workflows with IoT. This helps in integrating data from future and current connected
systems and devices. Highlighting the effect of these platforms on the current dynamics, the
author indicated that organizations incurred low costs for computing data and storing them on the
cloud platform. Even edge computing has been trending in the present scenario. It has also been
noted that with the help of these platforms, the costs of devices, connectivity, and sensors have
been reduced. These have further enabled the development of mobile application platforms and
smartphone penetration enhancement [27].
Intelligent platforms have also been optimally using interconnected and heterogeneous networks,
including the internet. These advancements have been possible with the successful development
of Radio Frequency Identification (RFID) technology along with wireless communication
technologies [28]. Concerning information system platforms, it has been understood that
“Intelligence may be contained completely within a device, combined with platform intelligence
in the cloud, or reside almost completely within a platform to which the device connects to
perform some functions” [28].
The data mining algorithm is a vital IoT platform, which is responsible for facilitating valuable
analytics, managing services and networks efficiently, and estimate future events precisely
irrespective of all constraints. Herein, it has been highlighted that when new raw data are
processed with the help of traditional data mining algorithms then accurate insights are not
gained. This is the reason why a responsive and intelligent environment is not established by the
system. In this context, it has been stated that “we predicted astronomically huge heterogeneous
network of IoT devices with data mining algorithms to subsist as a seamless fabric, covering and
synthesizing the intelligent environment” [31]. All these depict the importance of developing a
precise ‘data mining algorithm’ so that flexible, open, and dynamic ad-hoc IoT services can be
made possible. These algorithms when applied to input data can enable the extraction of personal,
as well as useful information. However, the fulfillment of all these aspects is highly challenging
concerning IoT [31].
IoT devices have been increasingly used for enhancing the lifestyle of people in society. They are
also useful in conserving energy, enhancing sectors such as health, agriculture, and
transportation, thereby adopting the smart approach. The data retrieved from those devices are
helpful in increasing knowledge on trends and patterns that further increase the efficiency of
companies and improve economies and the global community. Considering the usage of IoT and
its impact on the current dynamics, it has been understood that it enables exploiting data analytics
and big data. This helps in facilitating data preprocessing, combining, gathering, and categorizing
along with decision-making [38]. Besides, focusing on trailblazing DM, it has been found that the
10. International Journal of Wireless & Mobile Networks (IJWMN), Vol.14, No.3, June 2022
30
data mining framework is highly effective in applying IoT. In this concern, “IoT generates
enormous amount of heterogenous valuable data. To convert this data into knowledge, data
mining systems are developed” [39]. It has also been understood that there are several limitations
for considering IoT data, as it must be analyzed on a real-time basis. Therefore, improving
personal security in the future and enhancing people’s overall quality of life will require
considering effective solutions such as cloud computing and deep learning to derive knowledge
from new situations [40].
Besides, advancements in designing sensors are also found to be an important aspect. This is
because with improved sensors real-time data collection and analysis could be possible, which
further has contributed to the development of IoT dynamics along with that of DM. Specifically,
wireless sensor networks (WSNs) are increasing in importance, as it has contributed in
developing the quality of information, as well as communication technologies. These networks
have also been responsible for integrating and connecting the internet in a wide area of
application, for instance, industries [41]. Even Elkhodr et al. [30] acclaimed that “Todays’
sensors can monitor temperature, ambiance, soil makeup, pollution in the air, noise, presence of
objects or movements among other actuating functionalities triggered based on some sensed
information” [30].
6. THE USEFULNESS OF THE PRESENT RESEARCH
The findings presented have clearly shown that the existing research can benefit people’s
knowledge on the impacts of advancing the IoT dynamics and how it links to the DM aspects.
Besides, it has also been found that various platforms such as sensors are also getting evolved
with IoT, which, in turn, have led to the development of better IoT solutions for addressing all the
issues that have been persisting.
6.1. Added Value to Current Research
Herein, it needs to be mentioned that the information gathered from varied existing literature and
studies carried forth by numerous researchers have significantly added value to the current
research. This is because the general objectives of the research paper have been effectively
addressed. Besides, the exploration of future scope and implications of IoT and DM have
contributed to the existing literature, which makes the present research a significant resource for
future reference.
7. DISCUSSION
The findings and information gathered from the above sections have highlighted that IoT has
become an emerging technology and has an immense scope in enabling better solutions. The
above-made analysis also indicates that the IoT dynamics are ubiquitous and evolving. This has
been particularly understood by examining cross-cutting trailblazing DM [17], [27], [29]. With
these evolutions, several platforms associated with the IoT ecosystems have also been developed
in the current era. This includes devices, data generation, sensors, data compilation, information
system platforms, data mining algorithm, information system rollout, and an informed decision-
making process. Besides, their advancements are expected to be more evident in the future, which
will further enhance the outcomes [4], [28], [29], [30], [32], [33]. Additionally, developments
have also been evident in designing sensors. With the evolution of several technologies and
WSNs, the sensors are gradually becoming more intelligent [41].
11. International Journal of Wireless & Mobile Networks (IJWMN), Vol.14, No.3, June 2022
31
8. CONCLUSIONS
The preceding discussion has indicated that IoT is happening and has a significant implication on
data mining. All indications suggest that it will continue to grow and increasingly affect how we
interact with “things”. A backdrop of concerns exists. Some of the matters raised by researchers
include the rate of growth of the technology against the ability to regulate implementation,
challenges in standardization, information integrity, and data security [42], [43]. Accordingly, the
implications of IoT on data mining will continue to be felt in what can be described as an
unprecedented manner similar to what was mentioned in the paper, as many “things” continue to
be connected and communicated through IoT, a significant effect will continue to be noticed in
data mining.
9. FUTURE RESEARCH
The present study has effectively addressed the general objective throughout the paper. The study
understood that the IoT dynamics are ubiquitous, as the IoT has been evolving with time.
Particularly, by emphasizing data mining, it has been understood that the IoT ecosystem
platforms also evolved, which made the future implications more promising and effective for
making the life of people better. However, the present study still had some limitations. One of the
limitations was the exclusion of primary data. Hence, future researchers must consider primary
research for obtaining more accurate outcomes. Besides, the present study is found to be
qualitative. However, integrating statistical analysis with the help of quantitative research would
generate better results. Furthermore, the present research paper is found to be wider as it has
covered all the aspects of data mining and IoT ecosystems. However, with a more focused aim,
the research would have generated detailed information. Hence, these aspects need to be
considered in future research so that the study area is explored to the fullest.
REFERENCES
[1] Kong, D., Liu, D., Zhang, L., He, L., Shi, Q., & Ma, X. (2020). Sensor anomaly detection in the
industrial internet of things based on edge computing. Turkish Journal of Electrical Engineering &
Computer Sciences, 28(1), 331–346. doi:10.3906/elk-1906-55
[2] Welbourne, E., Battle, L., Cole, G., Gould, K., Rector, K., & Raymer, S. et al. (2009). Building the
internet of things using RFID: the RFID ecosystem experience. IEEE Internet Computing, 13(3), 48-
55. https://doi.org/10.1109/mic.2009.52
[3] Hancock, B., & Hancock, L. (2016). Somebody's watching: The ever growing internet of things. Phi
Kappa Phi Forum, 96(3), 12-15.
[4] Chen, F., Deng, P., Wan, J., Zhang, D., Vasilakos, A. V., & Rong, X. (2015). Data mining for the
internet of things: literature review and challenges. International Journal of Distributed Sensor
Networks, 1-14.
[5] Wu He, Gongjun Yan, & Li Da Xu. (2014). Developing vehicular data cloud services in the IoT
environment. IEEE Transactions on Industrial Informatics, 10(2), 1587-1595.
https://doi.org/10.1109/tii.2014.2299233
[6] Xia, F., Yang, L., Wang, L., &Vinel, A. (2012). Internet of Things. International Journal Of
Communication Systems, 25(9), 1101-1102. https://doi.org/10.1002/dac.2417
[7] Kim, M., Man, K. L., &Helil, N. (2019). Advanced internet of things and big data technology for
smart human-care services. Journal of Sensors, 2019, 1-3.
[8] Lee, I., & Lee, K. (2015). The Internet of Things (IoT): Applications, investments, and challenges for
enterprises. Business Horizons, 58(4), 431-440.
[9] Bin, S., Yuan, L., & Xiaoyi, W. (2010, April). Research on data mining models for the internet of
things. In 2010 International Conference on Image Analysis and Signal Processing (pp. 127-132).
IEEE.
12. International Journal of Wireless & Mobile Networks (IJWMN), Vol.14, No.3, June 2022
32
[10] Dachyar, M., Zagloel, T. Y. M., &Saragih, L. R. (2019). Knowledge growth and development:
internet of things (IoT) research, 2006–2018. Heliyon, 5(8), e02264.
[11] Ibarra-Esquer, J. E., González-Navarro, F. F., Flores-Rios, B. L., Burtseva, L., &Astorga-Vargas, M.
A. (2017). Tracking the evolution of the internet of things concept across different application
domains. Sensors, 17(6), 1379.
[12] Duan, Y., Lu, Z., Zhou, Z., Sun, X., & Wu, J. (2019). Data privacy protection for edge computing of
smart city in DIKW architecture. Engineering Applications of Artificial Intelligence, 81, 323-335.
[13] Cai, H., Xu, B., Jiang, L., &Vasilakos, A. V. (2016). IoT-based big data storage systems in cloud
computing: perspectives and challenges. IEEE Internet of Things Journal, 4(1), 75-87.
[14] Jara, A. J., Genoud, D., &Bocchi, Y. (2014, July). Big data for cyber physical systems: an analysis of
challenges, solutions and opportunities. In 2014 Eighth International Conference on Innovative
Mobile and Internet Services in Ubiquitous Computing (pp. 376-380). IEEE.
[15] Shi, W., Cao, J., Zhang, Q., Li, Y., & Xu, L. (2016). Edge computing: Vision and challenges. IEEE
Internet of Things Journal, 3(5), 637-646.
[16] Ren, J., Guo, H., Xu, C., & Zhang, Y. (2017). Serving at the edge: A scalable IoT architecture based
on transparent computing. IEEE Network, 31(5), 96-105.
[17] Ren, S., Hui, C. L. P., & Choi, T. M. J. (2018). AI-Based Fashion Sales Forecasting Methods in Big
Data Era. In Artificial Intelligence for Fashion Industry in the Big Data Era (pp. 9-26). Springer,
Singapore.
[18] Rabah, K. (2018). Convergence of AI, IoT, big data and block chain: a review. The Lake Institute
Journal, 1(1), 1-18.
[19] Li, Z., Wang, Y., & Wang, K. S. (2017). Intelligent predictive maintenance for fault diagnosis and
prognosis in machine centers: Industry 4.0 scenario. Advances in Manufacturing, 5(4), 377-387.
[20] Schimek, R. S. (2016). IoT case studies: companies leading the connected economy. American
International Group, 2-26.
[21] Misuraca, G. (2009). Futuring e-Government: Governance and policy implications for designing an
ICT-enabled knowledge society. ACM, 83-90.
[22] Kumar, R., Zhang, X., Khan, R. U., & Sharif, A. (2019). Research on data mining of permission-
induced risk for android IoT devices. Applied Sciences, 9(2), 277.
[23] Qiao, H., & Wang, G. (2012). Ananalys is of the evolution in Internet of Things industry based on
industry life cycle theory. Advanced Materials Research, 785-789.
[24] Saidu, C. I., Usman, A. S., & Ogedebe, P. (2015). Internet of things: impact on economy. Journal of
Advances in Mathematics and Computer Science, 241-251.
[25] Tsai, C. W., Lai, C. F., Chiang, M. C., & Yang, L. T. (2013). Data mining for internet of things: A
survey. IEEE Communications Surveys & Tutorials, 16(1), 77-97.
[26] Liu, C., Nitschke, P., Williams, S. P., &Zowghi, D. (2020). Data quality and the Internet of Things.
Computing, 102(2), 573-599.
[27] Deloitte. (2020). Internet of Things (IoT) The rise of the connected world. Deloitte Touche Tohmatsu
Limited, 3-33.
[28] Hassan, Q.F. (2016). Innovative research and applications in next-generation high performance
computing. IGI Global, 397-427.
[29] Gubbi, J., Buyya, R., Marusic, S., &Palaniswami, M. (2013). Internet of Things (IoT): A vision,
architectural elements, and future directions. Future Generation Computer Systems, 29(7), 1645-
1660. https://doi.org/10.1016/j.future.2013.01.010
[30] Elkhodr, M., Shahrestani, S., & Cheung, H. (2016). The internet of things: new interoperability,
management and security challenges. International Journal of Network Security & Its Applications
(IJNSA), 8(2), 85-102.
[31] Sunhare, P., Chowdhary, R. R., & Chattopadhyay, M. K. (2020). Internet of things and data mining:
An applications oriented survey. Journal of King Saud University-Computer and Information
Sciences, 2-22.
[32] Krishnamurthi, R., Kumar, A., Gopinathan, D., Nayyar, A., & Qureshi, B. (2020). An overview of iot
sensor data processing, fusion, and analysis techniques. Sensors, 20(21), 1-23.
[33] Brous, P., Janssen, M., Herder, P. (2018). Internet of Things adoption for reconfiguring decision-
making processes in asset management. Business Process Management Journal, 1-19.
[34] Perwej, Y., Omer, M. K., Sheta, O. E., Harb, H. A. M., &Adrees, M. S. (2019). The future of Internet
of Things (IoT) and its empowering technology. International Journal of Engineering Science, 20192-
20203.
13. International Journal of Wireless & Mobile Networks (IJWMN), Vol.14, No.3, June 2022
33
[35] Hussein, W. N. (2019). The Implementation Success Factors for IoT and Big Data Analytics in
Transportation System, IOP Conf. Ser.: Mater. Sci. Eng. 705 012049, 2019.
[36] Kumar, S., Tiwari, P., &Zymbler, M. (2019). Internet of Things is a revolutionary approach for future
technology enhancement: a review. Journal of Big Data, 6(1), 1-21.
[37] Venkatadri, M.,&Reddy, L.C. (2011). A review on data mining from past to the future. International
Journal of Computer Applications (0975 – 8887), 15(7), 19-22.
[38] Mudholkar, P., &Mudholkar, M. (2020). Internet of things (IoT) and big data: a review. International
Journal of Management, Technology and Engineering, 5001-5007.
[39] Gupta, P., & Gupta, R. (2017). Data mining framework for IoT applications. International Journal of
Computer Applications, 174(2), 4-7.
[40] Wlodarczak, P., Ally, M., &Soar, J. (2017). Data mining in IoT. Data Analysis for a New Paradigm
on the Internet, 1100-1103.
[41] Sheng, Z., Mahapatra, C., Zhu, C., & Leung, V. C. (2015). Recent advances in industrial wireless
sensor networks toward efficient management in IoT. IEEE Access, 3, 622-637.
[42] He, Y., Guo, J., & Zheng, X. (2018). From Surveillance to Digital Twin: Challenges and Recent
Advances of Signal Processing for Industrial Internet of Things. IEEE Signal Processing Magazine,
35(5), 120-129. https://doi.org/10.1109/msp.2018.2842228
[43] Tsai, C., Lai, C., &Vasilakos, A. (2014). Future Internet of Things: open issues and challenges.
Wireless Networks, 20(8), 2201-2217. https://doi.org/10.1007/s11276-014-0731-0
AUTHORS
Bongs Lainjo, MASc, Engineering, is an RBM systems consultant with expertise in
program evaluation. Bongs is a former UN Senior Advisor of Program Management,
Reproductive Health Commodity Security (RHCS) and Evaluation. Prior to that, he
worked for USAID as a Logistics and Management Information Systems Advisor
(LISA). He also served as COP/Senior Data Management Advisor for Columbia
University after spending close to a decade teaching as a professor at a number of
Canadian academic institutions. Bongs has worked in several countries in Africa,
Asia, Pacific Island Countries, Canada, and the United States.