Enterprise Iot
Article | July 20, 2023
Nothing is more innovative or sophisticated than the products being made by the wearables industry in the "smart" era. Individuals track, analyze, monitor, and transmit personal data using these tangible wearable gadgets. Moreover, the adaptable wearable technology is opening up new horizons with business-focused smartphone apps. However, it is still in its early stages, and according to recent developments in this field, the major players in wearable technology are concentrating on developing products with a focus on business applications.
These intelligent Internet of Things (IoT) devices are now widely employed in a variety of businesses and help detect biometric data such as heart rate and sleep habits, among others. In the coming ten years, wearable IoT technology or devices ought to become an integral part of every individual’s daily life.
Businesses around the world are incorporating the newest technologies into their functioning and are looking at digitally altering their impact in the market. With the majority of people already accustomed to using smartphones, they are now also getting familiar with utilizing wearable technology, such as smartwatches, jewelry, and fitness bands. Therefore, the demand for applications is increasing along with technology as we become more technologically adept.
Rising Wearable Industries
Health and Fitness Wearables
The health, fitness, and fashion industries are closely related to any wearable technology or device. People are now frequently using smartwatches to monitor their heart rate and the number of steps they take when walking or running, which has boosted the industries with this technology. IoT devices include medical sensors to track progress in terms of health. It is possible to determine how healthy a person's lifestyle is by gathering accurate health statistics from these devices. Additionally, it monitors sleeping patterns, enhancing your overall quest for wellness.
Gaming Wearables
Gaming is a significant new market for wearable technology and one which is booming. The most prevalent category of wearables in the market is virtual reality (VR) headsets. With VR devices like the Oculus Rift or Playstation VR, players are immediately immersed in otherworldly experiences. Several kinds of breathtaking experiences are now accessible to players everywhere, thanks to VR wearables.
Connected Cars
Automobiles are steadily gaining traction among IoT devices, but they are still a small market (just 0.05 percent of all connected devices are cars), and Ford and Tesla are vying for the top spot. Ford has dominated the connected car market, with Subaru being the only other manufacturer to see any appreciable growth in new connections since July 2020. In contrast, other producers are fighting for a sizable market share as the potential to grow this segment is highly exponential.
Conclusion
Today, wearable technology is planned, developed, distributed, and used in a variety of consumer and corporate markets. The ways in which these markets overlap and influence one another are constantly changing. IoT will significantly change how businesses engage with customers, streamline their operations, and contribute to the creation of a system that relies on such data.
Read More
IoT Security
Article | July 17, 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.
Read More
Industrial IoT, IoT Security
Article | July 12, 2023
Learn more about IoT data protocols and what makes them essential for a cohesive IoT ecosystem. This article will provide a detailed view of data protocols and their importance for modern businesses.
1 Significance of IoT Data Protocols for Business Operations
IoT ecosystems form an integral part of many businesses today, and IoT data protocols serve as the foundation for seamless communication and data exchange between connected devices. IoT protocols ensure the integrity and reliability of data, empowering businesses to make informed decisions, optimize operations, enhance productivity, and drive innovation. With standardized and secure IoT protocols and standards, companies can achieve efficient data transmission and allow for scalability across diverse IoT ecosystems. Understanding and leveraging the right protocols is essential for businesses to benefit from the full potential of their IoT investments and gain a competitive edge in today's interconnected world.
2 Understanding IoT Data Protocols
IoT data protocols are standardized rules and formats that ensure efficient and secure data transmission for efficient IoT communication. By adhering to established protocols such as MQTT, CoAP, and AMQP, businesses can maintain interoperability, scalability, and robust data transmission of IoT data, ensuring efficient data storage and management for their IoT ecosystem. This, in turn, empowers organizations to monitor and control critical processes in real-time and make informed decisions.
2.1 Role of IoT Data Protocols in the IoT Ecosystem
The seamless functioning of an organization's IoT ecosystem relies on the pivotal role played by IoT data protocols. These protocols, serving as the communication backbone, enable secure transfer and efficient data processing, thereby facilitating the seamless exchange of information within the IoT network. Consequently, businesses operating within the IoT sphere can harness the power of reliable data communication enabled by these protocols to unlock insights that drive innovation. IoT data protocols serve as the vital link that fuels the interconnected landscape of IoT devices, elevating the efficiency and efficacy of businesses as they navigate the complex web of IoT technologies and leverage its immense potential.
2.2 Overview of Common IoT Data Protocols
The IoT data protocols come with their own set of applications and challenges. Understanding each protocol's individual use cases will help businesses set up and scale their IoT device ecosystems.
MQTT (Message Queuing Telemetry Transport): MQTT is a lightweight and efficient protocol designed for low-power devices and unreliable networks. It uses a publish-subscribe model, making it ideal for IoT applications where bandwidth and power consumption are crucial factors, such as remote monitoring and control systems.
CoAP (Constrained Application Protocol): For resource-constrained IoT devices, CoAP is designed to enable smooth communication over the Internet. It uses a client-server model and is suitable for IoT applications where devices have limited processing power and memory, such as smart home automation, environmental monitoring, and healthcare systems.
HTTP (Hypertext Transfer Protocol): Although primarily designed for web applications, HTTP is also used in IoT systems for data transmission. The ubiquity and familiarity of HTTP make it a widely supported communication protocol. As a result, it is suitable for IoT devices that require high-level interoperability in applications that involve cloud integration, data analytics, and web-based control interfaces.
AMQP (Advanced Message Queuing Protocol): AMQP is a flexible messaging protocol ensuring reliable, secure, and interoperable communication between IoT devices and back-end systems. It supports both publish-subscribe and point-to-point messaging models, making it suitable for IoT scenarios involving complex routing, large-scale deployments, and enterprise integrations.
Zigbee: Zigbee is a wireless protocol designed specifically for low-power, short-range communication in IoT networks. It operates on the IEEE 802.15.4 standard and is known for its energy efficiency and mesh networking capabilities, leading to its widespread adoption in home automation, intelligent lighting, and industrial control systems.
3 Considerations for Choosing the Right IoT Data Protocol
Selecting a suitable IoT data protocol is essential to maintain smooth interoperability and a unified IoT ecosystem. Compatibility with existing infrastructure is crucial for seamless integration and cost-effective implementation. Security measures must also be robust to protect sensitive data from unauthorized access and potential breaches. Additionally, scalable and flexible data protocols in IoT are vital to accommodate future growth and evolving business requirements. Furthermore, the protocol's reliability and efficiency in transmitting data should align with the use case of IoT systems. Finally, considering the protocol's industry adoption and standardization level will also help minimize risks and enhance interoperability.
4 In Summary
IoT data protocols play a significant role in facilitating efficient and secure business operations within the IoT ecosystem. By learning more about the use cases of the most common protocols in the industry, businesses can consider factors such as compatibility, security, scalability, and reliability while choosing the most suitable option for their business. As IoT systems grow, more complex and reliable data protocols will emerge, paving the way for enhanced connectivity, interoperability, and transformative opportunities across various industries.
Read More
IoT Security
Article | June 27, 2023
Explore the world of readings on IoT security, to address complex cyber security challenges and privacy issues. It caters to a wide range of readers including industrialists, students & enthusiasts.
The Internet of Things (IoT) has revolutionized industries, enabling innovative applications and improved efficiency. However, along with the numerous benefits of the IoT comes the pressing need for robust security measures. As IoT devices become more prevalent and interconnected, their risks and vulnerabilities also increase. The experts in the domain must stay updated with the latest security practices and techniques to ensure IoT systems' integrity, confidentiality, and availability. A wide range of books has been explicitly tailored address these security concerns.
1. Analytics for the Internet of Things (IoT)
Author: Andrew Minteer
Analytics for the Internet of Things (IoT): Intelligent analytics for your intelligent devices provides a comprehensive guide for businesses aiming to make informed decisions and gain greater control over their IoT infrastructure. Written by an expert in the field, this book equips readers with the essential knowledge and techniques to solve the unique challenges associated with IoT and extract valuable insights from vast amounts of data. The book begins by tackling the complex task of extracting value from large volumes of often complex IoT data, empowering readers to make data-driven decisions. Strategies to address data quality concerns are discussed, ensuring that readers are equipped to handle the inherent challenges. It offers readers approaches to optimize business value and bring down costs. Scaling both data storage and analytics is a critical consideration in IoT deployments, and the book provides practical insights into handling scale effectively. The book covers a range of topics, including transmission protocols, data flow, value extraction, geospatial analytics, machine learning, and optimizing business value.
2. Industrial Internet of Things (IIoT)
Editors: R. Anandan, Suseendran Gopalakrishnan, Souvik Pal, Noor Zaman
One of the essential IoT security books, Industrial Internet of Things (IIoT): Intelligent Analytics for Predictive Maintenance comprehensively explores how the industrial internet is transforming through increased network agility and the ability to deploy, automate, integrate artificial intelligence, orchestrate, and secure diverse use cases at hyperscale. The adoption of industrial automation on a large scale is revolutionizing business processes, with the market for industrial robots projected to reach $73.5 billion by 2023. The book highlights how IoT industrial automation provides numerous advantages, including enhanced efficiency, high accuracy, cost-effectiveness among others. This book presents real-world case studies in IIoT, robotic and intelligent systems, and web-based applications. The content is tailored to appeal to a broad audience, including working professionals, educators, and researchers in various technical disciplines. The book provides industry leaders with valuable insights by proposing business models that revitalize the workforce.
3. IoT and OT Security Handbook
Authors: Smita Jain, Vasantha Lakshmi, Foreword: Dr Rohini Srivathsa
IoT and OT Security Handbook: Assess risks, manage vulnerabilities, and monitor threats with Microsoft Defender for IoT is a comprehensive guide that equips industrial security, IoT security, and IT security professionals with the knowledge and tools to effectively address cybersecurity challenges in the rapidly evolving world of IoT and OT. In the era of the Fourth Industrial Revolution, where digital transformation and connected industries dominate, the book sheds light on the pressing security concerns that must be addressed to ensure data protection and operational resilience. Through a deep dive into the Purdue model of reference architecture, readers gain a solid understanding of common cyber-attacks prevalent in IoT and OT environments. The centerpiece of the book revolves around Microsoft Defender for IoT, a powerful security solution specifically designed to safeguard IoT and OT ecosystems. Furthermore, the concept of zero trust, which is crucial for establishing a robust security foundation, is thoroughly explored with practical insights on its implementation in the context of IoT devices.
4. Practical Internet of Things Security
Author: Brian Russell, Drew Van Duren
Practical Internet of Things Security: Design a security framework for an Internet connected ecosystem is an indispensable guide that navigates the complex realm of securely building and deploying systems in our IoT-connected world. The book primarily targets IT security professionals, security engineers, and individuals responsible for ensuring the security of their organization's data in the IoT landscape. However, it also serves as a valuable resource for business analysts and managers seeking to understand and address the security challenges associated with IoT deployments. Readers will gain a wealth of knowledge and practical skills, including breaking down cross-industry barriers, building a rock-solid security program, applying systems security engineering and privacy-by-design principles, and harnessing cloud-based systems. It delves into the unique security challenges associated with IoT and provides practical guidelines for architecting and deploying a secure IoT ecosystem within an enterprise.
5. IoT: Security and Privacy Paradigm (Internet of Everything (IoE))
Editors: Souvik Pal, Vicente García Díaz, Dac-Nhuong Le
IoT: Security and Privacy Paradigm is a comprehensive and authoritative resource that explores the evolution of security and privacy issues within the realm of the IoT. This book serves as a single reference point for students, researchers, and practitioners seeking to better understand the IoT security platforms and privacy landscape. The book adopts security engineering and privacy-by-design principles to design and implement robust cyber-security solutions within IoT ecosystems. It takes readers on a journey, starting with exploring security issues in IoT-enabled technologies and their practical applications. The book provides practical guidance on tackling security challenges and constructing a secure infrastructure for IoT devices. The book thoroughly discusses security challenges and solutions in areas such as RFID, WSNs, and IoT. The primary audience for this book includes specialists, researchers, graduate students, designers, experts, and engineers focused on security-related issues and research.
6. IoT Security Issues
Author: Alasdair Gilchrist
IoT Security Issues addresses the rapid proliferation of internet-connected devices, where security often takes a backseat to product development. This book delves into the inherent vulnerabilities and IoT security challenges, offering insights on how to address and mitigate these issues. By examining the root causes of these problems and emphasizing the importance of programming and security best practices, the author presents practical solutions to combat the lax security processes prevalent in the IoT landscape. This book caters to a wide range of readers, including programmers who have yet to focus on the IoT, security professionals, and individuals with a keen interest in hacking and making. While a basic programming background would be beneficial for certain chapters later in the book, the core content is explained in a manner that is approachable for readers from various backgrounds.
7. Security and Privacy Issues in IoT Devices and Sensor Networks
Editors: Sudhir Kumar Sharma, Bharat Bhushan, Narayan C. Debnath
This book, of all the IoT security books, delves into the critical aspects of security breaches in IoT and sensor networks, offering a comprehensive exploration of potential solutions. The book takes a two-fold approach, thoroughly examining the fundamentals and theoretical foundations of sensor networks and IoT security. It then explores the practical IoT security solutions that can be implemented to enhance the security of these elements, providing illuminating case studies to reinforce understanding. The book is an invaluable resource for industry professionals working with wireless sensor networks (WSN) and IoT systems, enabling them to elevate the security of these interconnected systems. Additionally, researchers, material developers, and technology specialists grappling with the intricate nuances of data privacy and security enhancement will find the book's comprehensive information highly beneficial.
Final thoughts
IoT security for professionals involves implementing secure communication protocols, strong authentication, device management, data encryption, access control, and regular security audits. It is crucial to stay updated, maintain a security-aware culture, and prioritize the ongoing monitoring and adaptation of security measures to address emerging threats.
The above listed books delve into various aspects of IoT security, providing insights, strategies, and practical solutions to mitigate risks and protect IoT ecosystems. This article highlights some essential IoT security books that are indispensable resources for IoT professionals striving to enhance the security posture of their organizations. They also provide real world case studies, best practices and strategies to minimize risks.
Read More