Industrial IoT, IoT Security
Article | July 12, 2023
For businesses to grow, they must be armed with the right technology and implement the right strategies to get a high return on their investments. With an IoT strategy, you can successfully make sense of the high volumes of data generated. IoT is about having devices with sensors communicate with other devices over the internet and share real-time data or parameters to maintain healthy system processes. Sharing and transferring data in real time over the cloud creates a lot of data that needs to be carefully managed.
Not having a streamlined method to control and manage the volume of data to capture, send, transmit, and receive over the cloud poses many space constraints as the data piles up quickly. Furthermore, deciding what data to keep and what to discard, how long you need the data, and for what purpose are all critical. Some standard IoT devices include sensors, lights, alarms, and cameras that a smartphone can control.
Learn about the importance of data management in establishing an IoT framework below.
The Top Reason for Establishing an IoT Framework Needs Data Management
Learning from past data trends to make future decisions in an IoT framework is critical. Data management acts as a layer between the IoT devices generating the data and the software accessing the data for analysis and services. It helps review, analyze, and navigate the massive amounts of structured and unstructured data. Defining which actions trigger responses to create data in your process is necessary to monitor your product and services and to keep your customers satisfied. In an IoT framework, managing the large amounts of data that are generated and collected means learning from the past and predicting what will happen in the future.
Why is Data Management for the IoT Framework Crucial for Medium and Large Enterprises?
Creating a better product is essential to add more value to your product offerings and avoid recalls, keeping your brand reputation at stake. The more data, the deeper the analysis, and the more refined the product, the greater the need to manage large amounts of data efficiently.
The future of IoT data management is promising when it comes to improving all aspects of your business processes, mainly controlling the automation and manufacturing processes and software triggers. Check out the in-depth benefits of data management in IoT.
Data management in IoT helps conduct a field test of your IoT products before deployment.
Improve the uptime of your business production lines and equipment.
Perform seamless decision-making for planning, scheduling, and execution systems to meet the changing customer and market demands using accurate and current data.
Data management helps efficiently deploy IoT solutions such as enterprise resource planning (ERP), enterprise asset management (EAM), and manufacturing execution systems (MES) in manufacturing businesses.
Data management helps remote monitoring of automation systems and robotic systems in industrial IoT needs current data and management.
Improve production flexibility and responsiveness by welcoming smart manufacturing using IoT data management.
When it comes to the data management of IoT devices, different types of data management systems take care of structured and unstructured data.
8 Data Management Systems for Your Enterprise IoT Devices
IoT device management means registering, organizing, monitoring, and remotely managing IoT-connected devices at scale. Various cloud architectures with different data management systems help with efficient IoT device management. In addition, equipment data, sub-meter data, and environmental data help track the performance of your IoT devices through IoT data collection. Let's find out how data management systems for IoT devices would help develop an IoT strategy for your large enterprise.
IoT gateway device management involves many steps in keeping your operations healthy and maximizing uptime. These are provisioning, authentication, configuration, control, monitoring, diagnostics, software updates, and maintenance. In addition, data management systems aim to make data available for analysis in the long term. The different data management systems are as under:
Querying
Production
Collection
Aggression/Fusion
Delivery
Pre-processing
Storage, updating and archiving
Processing or analysis.
These data management systems capture, organize, store, retrieve, and analyze data when required. Sorting out the data management in IoT will initiate your internet of things database scalability. An IoT data lifecycle is built around the data management systems in the data flow, which acts as guidelines or checkpoints for a smooth data flow across your IoT platform. Let us unfold them below.
Seven Guidelines for Cost-Effective IoT Data Management
• Querying: Accessing and retrieving data for temporary monitoring. For example, you could ask IoT devices or sensors for data in real time to learn more about trends and patterns.
• Production: Sensing and transferring data by the "things" or IoT devices in an IoT framework is the data production phase. Pushing the data to the cloud network and the IoT database servers and reporting it to the interested parties. This rich data has different formats such as audio, video, or image content, and is time-stamped and geo-stamped.
• Collection: Collecting and retrieving data for a predefined time interval and sharing it with the governing components within the gateways is a part of the collection. Filtering out valuable data and compressing it accordingly helps seamless data transfer. It is also a part of data collection.
• Aggression or fusion: Part of the aggression is real-time data transmission across the network to increase the rate of data streaming over the limited bandwidth. It pulls together information from different points of contact and reduces the amount of information that needs to be stored and sent.
• Delivery: Collating the data from multiple touch points across the IoT framework and summing it up for the final responses is a part of the data delivery management system. Making data ready for permanent data storage is also a part of it.
• Preprocessing: Removing redundant, missing, and incomplete data and making all the data unified is a part of preprocessing. Data cleaning is also one of the preprocessing methods applied to data mining.
• Storage, Update, and Archiving: Storing data in an organized way for long-term offline usage or big-data systems is a part of the storage data management system. It can be decentralized or centralized as per the required capabilities.
• Processing or Analysis: Retrieval of stored packets of data accessed for an efficient analysis is a part of data processing or analysis in a data management system.
Whenever handling large amounts of data, an efficient data management system will solve numerous problems concerning your IoT strategy, as discussed above. Find out exactly what can keep you from implementing IoT.
5 Growth Challenges in Data Management for IoT Technology
High Initial and Ongoing costs:
Upgrading the hardware and software infrastructure that is already in place, hiring IoT-trained staff, and building an IoT infrastructure will all require upfront and ongoing costs.
Vulnerability:
Your IoT security strategy is a critical aspect of your IoT platform strategy. Multiple data points for structured and unstructured data captured, transmitted, stored, and retrieved by software come with security risks.
Procuring Quality Hardware:
Finding compatible hardware for your requirements and building an infrastructure around them can take a while regarding decision-making for scalability. In addition, hardware must remain supportive of the quick adoption of future software innovations.
Installation and Upkeep of Hardware Infrastructure:
Setting up a complex IoT strategy with the implementation of IoT data management, infrastructure, security, and more takes time and expertise. One of the other big worries is keeping the hardware infrastructure in good shape so that security can't be broken.
Constraints on Scalability and Agility:
The humungous IoT data traffic poses a severe concern for appropriate control of the data storage, retrieval, analysis, monitoring, and everything aligned with IoT data management. Also, the fact that IoT data doesn't last as long as other types of data is a risk to the way data flows and is collected.
Now, let us figure out how to implement IoT that aligns with your business objectives.
How to Implement IoT in Line with Your Business Goals
A complete analysis of your immediate and long-term business objectives is critical as it helps decide which data to keep and which to discard after how much time. Every byte of data you hold and analyze comes with a cost for storage, retrieval, and security, which can be a barrier to implementing IoT for your business. Identifying IoT data collection helps you align your IoT implementation strategy with your business objectives. Here are a few ways to address your implementation of IoT.
Consider the use cases of IoT data management as per the processes involved in your business.
Implement security protocols for encryption and restricted access as per the type of business data.
Organize training for the existing workforce and hire skilled professionals in IoT.
Understand your business's data requirements, including the data collection process.
Allow enough budget for IoT infrastructure and resources.
Consider the design and development of the product as per the customer's behavior.
Consider the impact of the environmental conditions affecting your business.
Measure real-time performance metrics using a suitable IoT sensor to streamline your process.
Take automated decisions with the help of AI once IoT sensors recognize the performance gaps.
Choose the right IoT platform that defines how you communicate and handle data.
Understand that IoT implementation is a complex process and needs commitment.
Collect only the important data and statistics for a smooth workflow and to lower the cost of putting IoT into place.
Taking into account where your storage and production lines are located, choose the best ways to gather, organize, and analyze your data.
Use cold path analytics for the long term and hot path analytics for real-time data storage.
Building infrastructure with scalability in mind will help small businesses grab market share quickly and efficiently. As a result, medium-sized enterprises will find prominence in their industry. Using data visualization in business intelligence allows for rapid optimization of your IoT devices and for controlling data management costs in the long run without negatively impacting performance. Explore more about IoT data visualization down below.
Role of Data Visualization in IoT for Business Intelligence
With IoT data visualization, you can optimize business processes by applying visualization business intelligence to get your business ready to scale. Discover the role of data visualization in your IoT strategy.
Make sense of the data you've collected or saved.
Patterns and trends should be recognized.
Check the data for inconsistencies and errors. The output should then be visualized over time for analysis and monitoring.
IoT infrastructure and devices improve performance and streamline the IoT data flow.
Analyze real-time data correlations across multiple business verticals using the IoT communication platform.
Make future decisions based on the data captured in the past.
Get actionable insights on customer behavior and
Identify the factors impacting your business.
Once you identify the gaps in business processes, you can make changes to the process and further improvise. Creating an optimized workflow and detecting errors and faults in a process early are the primary goals of data management in an IoT strategy. Tackling vulnerabilities in data security and data redundancy helps the cost-effective implementation of IoT for small businesses, opening avenues for scalability. With IoT data management, you can also optimize your products to make customers happier and get a bigger share of the market, which is great for your business's growth.
Summarizing
With secure access control, encryption, software updates, endpoint security, and communication protocols in place, the relentless power of data visualization for analyzing and monitoring the captured data has proved to be unmatched. Bringing resilience and giving a rapid boost to the scalability of your medium and large enterprises is now becoming a norm with organized IoT data management.
FAQs:
• What is the most significant benefit of IoT?
IoT helps devices or sensors report real-time data for smooth interconnected production operations. In addition, IoT keeps healthy functions throughout and minimizes the turnaround time for troubleshooting and maintenance.
• What are the three types of IoT?
Depending upon the needs from time to time, the three types of IoT include short form, medium form, and long form. The short form meets immediate needs, the medium form meets future needs, and the long form keeps the system running smoothly.
• How does data analytics help IoT?
Effective process optimization is possible by analyzing the data generated in an IoT framework. It helps boost efficiency, and connectivity, cut costs and unlock scalability.
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IoT Security
Article | July 17, 2023
Explore the events on IoT security, addressing to the complex cyber security challenges and privacy issues. It caters to a variety of attendees including industrialists, students and enthusiasts.
The significance of IoT security cannot be overstated in today's interconnected business landscape. Safeguarding sensitive data and mitigating risks is paramount, making robust IoT security a non-negotiable imperative for organizations seeking to thrive in the digital age.
From industry professionals seeking to expand their knowledge to builders and buyers in the market, these events provide a comprehensive platform to learn, connect, and discover the possibilities of scaling with IoT. Attendees can connect with buyers, sellers, and innovators, fostering meaningful connections and exploring potential business opportunities. At these industrial IoT conferences 2023 and beyond, attendees can immerse themselves in a vibrant atmosphere of innovation and collaboration.
1. IoT Tech Expo
September 26-27, 2023 | RAI (AMSTERDAM)
The IoT Tech Expo Europe is a prominent event that serves as a platform for exploring the latest innovations, solutions, and strategies in the field of IoT, digital twins, enterprise transformation, IoT security, and edge platforms. It promises two days of top-level content and thought leadership discussions. Industry experts, including keynote speakers and panelists, will share their unparalleled industry knowledge, real-life experiences, and insights through solo presentations, expert panel discussions, and in-depth fireside chats. Some of the key sessions will include panel discussions on staying on track with digital twins, examining their pitfalls across industries, and exploring the incorporation of other technologies like AI, ML, and Blockchain for agile processes. Notable speakers in this domain include Bruno Ávila, i-Team Director - Digital Urban Planning Lab, City of Amsterdam; Ben Lomax Thorpe, Head of Digital Twin, among others. Additionally, the event showcases success stories and case studies from organizations leading the way in digitalization and IoT implementation.
2. International Conference on the Internet of Things
November 7-10, 2023 | Nagoya (Japan)
This event brings together leading researchers, industry experts, and stakeholders in the IoT field. This conference serves as a platform for visionary and groundbreaking research, fostering innovation in various IoT verticals such as smart industry, smart cities, smart health, and smart environment. The 13th International Conference on the Internet of Things (IoT 2023) will include keynote speeches, research presentations, panel discussions, and interactive sessions. It will provide a platform for sharing visionary ideas, ground-breaking research findings, and innovative solutions in the realm of IoT and related fields. Nagoya, the host city for IoT 2023, will offer a captivating setting for the conference. With a focus on visionary research and innovation, the conference provides a platform for knowledge sharing, collaboration, and exploration of IoT advancements in various verticals.
3. 9th Annual IoT Security Foundation Conference
November 7, 2023 | IET (London)
The 9th Annual IoT Security Foundation Conference is a highly regarded event dedicated to IoT cybersecurity. With the increasing prominence of artificial intelligence in various industries, this year's conference will focus on the impact of AI on cybersecurity, exploring its implications for developers and cyber defenders at the forefront of the field. The call for presentations is currently open, inviting submissions on a wide range of IoT security-related themes till July 14th, 2023, with notifications of acceptance to be sent by August 18th, 2023. By participating in the IoTSF 2023 Conference, sponsors and exhibitors gain exposure within the IoT security community and can forge new customer relationships, generate leads, establish partnerships, and strengthen existing customer connections. The conference will cover a range of themes, including business, technical, operational, educational, and policy-related topics. Proposals are invited on these subjects, offering speakers an opportunity to contribute to the diverse interests of conference attendees.
4. ETSI IoT Conference 2023 (ETSI IoT Week 2023)
July 4-6, 2023 | Sophia Antipolis (France)
ETSI, the European Telecommunications Standards Institute, is organizing its annual flagship event, the ETSI IoT Conference. The conference, ' IoT Technologies for Green and Digital Transformation,' is a must-attend event for professionals involved in the Internet of Things, recognizing the significance of standard-enabled technologies for IoT service deployments. It provides a valuable platform for attendees to learn and share experiences related to IoT technologies, services, activities, and requirements, focusing on current and future standardization efforts. The 2023 edition of the conference will feature a combination of keynote speeches, presentations, interactive panels, and IoT demonstrations, creating ample networking opportunities for participants. The event will revolve around three main areas: IoT for the digital and green transformation, IoT technologies, and horizontal IoT standards for various vertical business sectors. The ETSI IoT Conference is particularly relevant for organizations and stakeholders interested in the service and operational aspects of IoT, including industry representatives, SMEs, research and development institutions, academia, decision and policy makers, as well as users of IoT standards such as cities, governments, and societal actors.
5. 4th International Conference on Big Data, Machine Learning and IoT (BMLI 2023)
August 26-27, 2023 | Dubai (UAE)
The 4th International Conference on Big Data, Machine Learning, and IoT serves as a major platform for presenting innovative ideas, developments, research projects, and approaches in the domains of big data, machine learning, and the internet of things. This event includes but is not limited to big data techniques, models, and algorithms; infrastructure and platforms for big data; search and mining in big data; security, privacy, and trust in big data. Authors are invited to submit original papers by July 01, 2023, through the conference's submission system. Additionally, selected outstanding papers will have the opportunity to be considered for publication in renowned journals such as the International Journal of Database Management Systems (IJDMS), the International Journal of Data Mining & Knowledge Management Process (IJDKP), and others. The event will provide an excellent opportunity for researchers, industry professionals, and practitioners to explore the latest advancements, share knowledge, and foster collaborations in the dynamic fields of big data, machine learning, and IoT.
6. 28th Australasian Conference on Information Security and Privacy (ACISP 2023)
July 5-7, 2023 | Brisbane (Australia)
The 28th Australasian Conference on Information Security and Privacy (ACISP 2023) is an event in the field of cybersecurity and privacy, bringing together researchers, practitioners, and industry experts from Australasia and around the world. This conference will serve as a platform to exchange innovative ideas, research findings, and advancements in information security and privacy. ACISP 2023 focuses on addressing the evolving challenges and emerging trends in the field, providing a forum for discussing theoretical and practical aspects of IoT security risks. Participants have the opportunity to present their research papers, engage in enlightening discussions, and network with professionals in the industry. The conference covers a wide range of topics related to information security and privacy, including cryptographic protocols and algorithms, security in emerging technologies, intrusion detection and prevention.
7. The Things Conference
September 21-22, 2023 | Amsterdam (Netherlands)
The Things Conference is dedicated to LoRaWAN, attracting thousands of professionals and enthusiasts worldwide. This highly anticipated gathering will serve as a hub for the entire LoRaWAN ecosystem, offering a unique opportunity to meet key players, gain valuable insights into the IoT industry, and explore the expanding LPWAN market. The event showcases a diverse range of LoRaWAN enabled security IoT devices and gateways at the Wall of Fame, where participants can interact with and experience first-hand the latest products from over 100 partners. The conference program features an impressive line-up of speakers from prominent companies such as Blues, Miromico, ELSYS, TagoIO, Edge Impulse, and more. Attendees can benefit from engaging keynotes, insightful workshops, interactive side sessions, case studies, and value-driven stories. These sessions cover various aspects of LoRaWAN, offering attendees valuable knowledge and practical guidance. One of the highlights of The Things Conference is The Things Certifications, which allow participants to showcase their expertise.
Final Thoughts
The conferences help industry experts, IT professionals, engineers, and decision-makers to gain insights and in-depth knowledge. Attendees can expect a comprehensive program consisting of keynote presentations, panel discussions, case studies, and interactive workshops. The above events will cover various topics, concerning the IoT security. Participating in these will provide networking opportunities, allowing attendees to connect with peers, share experiences, and establish valuable business connections. Leaders can stay updated with the evolving data center landscape and gain a competitive edge in their evolving technologies, to provide protection against threats.
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Industrial IoT, IoT Security
Article | July 11, 2023
As consumer demands evolve, fleet managers are turning to IoT to deliver products faster and more efficiently. The progress being made in edge computing represents the full potential of IoT: the power of data on the move. However, operating on the edge also reveals some of IoT’s greatest challenges: maintaining network security as the number of endpoints multiplies; rethinking traditional business models as industries become increasingly interdependent; and, perhaps most importantly, establishing a seamless, reliable network across borders, cultures, and regulatory environments.
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Enterprise Iot, Infrastructure
Article | May 31, 2023
Discover the crucial role of big data capabilities in unlocking the potential of IoT for businesses. This article covers their synergy, challenges, and value in decision-making and revenue generation.
Contents
1 Why Big Data and IoT Matter for Businesses
2 Understanding Synergy of Big Data and IoT
2.1 How IoT generates Big Data
2.2 Challenges of Processing Big Data from IoT Devices
2.3 Importance of Big Data in IoT Applications
3 The Value of Big Data and IoT for Businesses
3.1 Improved Decision-making for Businesses
3.2 Generate New Revenue Streams
4 Final Thoughts
1. Why Big Data and IoT Matter for Businesses
The internet of things (IoT) is connecting all types of physical assets to the internet, from smart wearables that track wearer’s vitals to connected industrial units that can report any malfunctions automatically. Big data in IoT is a natural outcome with the growth of IoT devices, with an immense surge in the amount of data being generated.
There are currently over 13 billion connected IoT devices worldwide.
(Source – Techjury)
This data is extremely valuable to businesses as it can help streamline operations, predict trends, and diagnose device issues. Certain functions of IoT devices that are crucial for modern businesses, such as enabling predictive maintenance, depend on the analysis of the data generated every second. However, to maximize the ROI from their IoT ecosystem, businesses must first manage and process the vast amounts of unstructured data they produce. This is where big data capabilities come in.
2. Understanding Synergy of Big Data and IoT
Big data and the IoT are fundamentally different concepts, but are closely connected. Big data is a term that is used for a great amount of data that is characterized by volume, velocity, variety and veracity (or the ‘trustworthiness’ of data). The IoT is a term for physical devices or objects linked to the internet using an assortment of technologies. Understanding the synergy between these two technologies will be critical for businesses looking to leverage their full potential.
2.1 How IoT generates Big Data
IoT is one of the primary drivers of big data growth. The vast number of interconnected devices in the IoT ecosystem generates a massive amount of data every second. This data includes information on user behavior, device performance, and environmental conditions, among others.
The nature of this data makes it challenging to store, process, and analyze using traditional data management tools. This is where big data technologies such as Hadoop, Spark, and NoSQL databases come in, providing the ability to manage massive amounts of data in near-real-time, enabling critical applications of big data in IoT. For businesses, processing IoT data is synonymous with processing big data, due to the nature of the data generated by an IoT ecosystem.
2.2 Challenges of Processing Big Data from IoT Devices
IoT data processing is a complex and challenging task due to several reasons. Firstly, the sheer volume of data generated by these devices is enormous and is only increasing. This requires a robust infrastructure and specialized tools to store, manage, and analyze the data efficiently.
This data is also generally unstructured, heterogeneous, and complex, making it difficult to process using traditional data management and analysis techniques. Moreover, it is often noisy and may contain errors or outliers, which can impact the accuracy of data analysis. Businesses also face a challenge when securing such vast amounts of data. Since IoT devices collect sensitive information such as personal and financial data at scale, it is critical to ensure that data is encrypted, transmitted securely, and stored safely.
Additionally, IoT devices often operate in remote locations with limited connectivity, making it challenging to transmit data to the cloud for storage and analysis. As IoT devices continue to proliferate and generate increasingly large amounts of data, businesses must adopt big data technologies to gain actionable insights from this data.
2.3 Importance of Big Data in IoT Applications
There are several use cases of the IoT where processing large amounts of data is essential. It plays a critical role in IoT applications, providing businesses with valuable insights that can be used to optimize processes, reduce costs, and improve overall efficiency. By collecting and analyzing large amounts of data from IoT devices, businesses can gain a better understanding of customer behavior, machine performance, and other critical metrics.
For example, big data in IoT can be used to identify patterns in customer behavior, allowing businesses to tailor their marketing efforts and improve customer engagement. Additionally, IoT devices can be used to collect data on machine performance, allowing businesses to identify potential problems before they occur, minimize downtime, and optimize maintenance schedules. The value of big data in IoT applications lies in its ability to provide businesses with real-time insights that can be used to drive growth, reduce costs, and improve overall efficiency.
3. The Value of Big Data and IoT for Businesses
Businesses looking to integrate big data in IoT must first consider their data storage and analytics capabilities. By understanding the value of big data technology in capturing and analyzing IoT-generated data, businesses can unlock insights that can help them make better decisions, optimize processes, and create new business opportunities.
3.1 Improved Decision-making for Businesses
IoT and big data technologies offer businesses a wealth of data that can be used to make better-informed decisions. By integrating IoT sensors and devices with their operations, businesses can collect real-time data on customer behavior, operational performance, and market trends. This data can then be analyzed using big data analytics tools to generate valuable insights that can inform decision-making.
For example, operational data can be analyzed to identify inefficiencies and areas for optimization, helping businesses reduce costs and improve efficiency. With the right data storage and analytics capabilities, businesses can leverage the power of IoT and big data to gain a competitive advantage and make better-informed decisions that drive growth and success.
3.2 Generate New Revenue Streams
By leveraging the vast amount of data generated by IoT devices and analyzing it with big data analytics tools, businesses can gain insights into customer behavior, market trends, and operational performance. These insights can be used to create new revenue streams and business models, such as subscription-based services, pay-per-use models, and predictive maintenance services.
For example, IoT sensors can be used to collect data on equipment performance, allowing businesses to offer predictive maintenance services that help prevent equipment breakdowns and reduce downtime. Similarly, customer data can be analyzed to identify new revenue opportunities, such as personalized product recommendations and targeted advertising. With the right strategy and investment in IoT and big data technologies, businesses can unlock new revenue streams and create innovative business models that drive growth and success.
4. Final Thoughts
Big data in IoT is becoming increasingly important for businesses, and the future prospects are bright. As IoT continues to grow and generate more data, businesses that can effectively analyze it will gain a competitive advantage, leading to increased efficiency, reduced costs, and higher ROI. To fully realize the benefits of IoT, businesses must develop big data analytics and IoT devices in tandem, creating a feedback loop that drives continuous improvement and growth. By embracing these technologies, businesses can make data-driven decisions and unlock new insights that will help them thrive in the years ahead.
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