Industrial IoT, IoT Security
Article | July 12, 2023
The biggest IoT trends are likely to manifest in 2022 and beyond.
1. BLOCKCHAIN
The term blockchain is a new concept and is known as a single registry; agreed and distributed in several nodes of a network that will continue in force in the coming years in various activities.
2. MOBILE COMMERCE OR M-COMMERCE
It is part of electronic commerce that is carried out exclusively through mobile devices such as smartphones or tablets. The processes will be specialized. With mobile commerce comes the need for device management. Device management is a vital step to ensure security is promptly implemented.Mobile Device Management (MDM) solutions, also known as MDM, offer brilliant benefits across all areas.
3. TELEWORK AND DISTANCE EDUCATION
Academic and work activities that are carried out remotely, preferably from home, will continue to be applied in a fixed or hybrid way. A smart device(s) can be used from a remote location and therefore enable workers to more effectively manage time.
4. ROBOTIC PROCESSING AUTOMATIZATION
It is all technology-oriented to the use of software, with the aim of reducing human intervention in the use of computer applications, especially in repetitive tasks. This reduces the risk of human error and will also cut down management costs.
5. ARTIFICIAL INTELLIGENCE
It is the combination of algorithms proposed with the purpose of creating machines that have the same capabilities as humans, with the aim of doing a variety of tasks. If we decide to develop an Artificial Intelligence that has greater intelligence, responsibility and scalability, we can make the most of learning algorithms and interpretation systems. In this way, we are able to create value more quickly and with a greater business impact.
It is essential to have new techniques that achieve smarter AI solutions, that require less data, with greater ethical responsibility and more resilience.”
Gartner
6. DIGITAL TRANSFORMATION
Digital transformation is the change associated with the application of digital technologies in all aspects of human society, and especially in organizations. Accelerating business digital transformation requires entrepreneurs to step back and re-evaluate their plans. It’s about aligning the customer experience strategy with coordinated and detailed digitization plans of what needs to be done, by whom and when. To do this, having precisely identified the customer journey of your digital customer allows you a complete approach, for which tools such as the customer journey map is key.
7. FINTECH
It is a nascent industry in which companies use technology to provide financial services in an efficient, agile, comfortable and reliable way. They aim to expand bank penetration.
8. DATA ANALYSIS
It is the process by which raw data is analyzed in order to answer questions and reach practical conclusions that support an organization’s decision-making. Using predictive models and AI tools, we can run simulations that are based on real scenarios and information. Thanks to this, we obtain data on contexts that would be difficult, very expensive or impossible to test in physical environments. Big data is big money.
9. SOFTWARE DEVELOPMENT
Software development is generally considered part of the agile family of approaches, and is often used in combination with one or more other methods. Softwareon a smart device can also be upgraded to include better connectivity. In addition to its development, there is likely to be more outsourcing also.
10. ADVANCED MANUFACTURING OR INDUSTRY 4.0
It refers to a new business model in which the interconnection of integrated ICT systems both with each other and with the internet is key. The adoption of Industry 4.0 technologies and the training of personnel will be the greatest opportunities that industries, companies and governments will have in the next decade. Therefore, 2022 represents the next step to embrace technological transformation as an indispensable element for competitiveness, resilience, and development.
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IoT Security
Article | July 17, 2023
The COVID-19 pandemic turned the tides towards remote work and virtual connectivity. And even though growth seemed to have slowed down in 2020, experts see double-digit growth in the next few years. The tides may be turning but virtual connectivity and the tools required for remote growth are not slowing down in demand. As the tech world adapts to new shifts, IoT is among one of the most anticipated technologies to prosper in 2021.
Digital transformation has rapidly accelerated in the past year and if the experts are to be believed, 2021 shows promise for an even better year for technological advancement. According to IDC’s 2020-2024 forecast, spending will reach an annual growth rate of 11.3 percent. And with this, the number of connected devices is likely to grow up. Take a look at what will be the focus of IoT industry trends in 2021.
Privacy & Security
As smart homes are becoming the norm and you cannot throw a stone without hitting a smart device, one thing is clear—IoT devices are everywhere. People almost always forget smartphones when talking about IoT devices, but the fact is that smartphones are very much a part of the IoT ecosystem. And with the infusion of IoT in our everyday lives, questions about privacy and security are cropping up.
Just recently, as WhatsApp announced its new privacy policy, millions of users planned to migrate to other alternatives. This led to WhatsApp pushing back its privacy update and tech businesses taking note of changing winds.
In 2021, privacy and security will be at the forefront of IoT industry trends, as devices infuse further into the everyday lives of people. According to recent research, 90 percent of consumers lack confidence in IoT device security. And the onus of bolstering consumer confidence will be up to IoT businesses.
Workforce Management
According to Gartner’s “Top Strategic Technology Trends For 2021” report, IoT will be a large part of the office experience in 2021. As businesses are trying to avoid the losses that occurred in early 2020, workplaces are being geared up with RFID tags, sensors, and monitors to ensure social distancing measures, whether employees are wearing masks and overall health monitoring.
Additionally, many organizations have decided to move permanently to a remote mode and will rely more on IoT devices for connectivity. So we can expect better automated scheduling and calendar tools, more interactive video conferencing, and virtual meeting technology. In the case of fieldwork, IoT will offer an added factor of monitoring behavior.
Greener IoT
Experts predict that energy will be a crucial factor in the IoT industry trends in 2021. With smart grids, metering, and restoration resilience being powered by IoT, 2021 will move towards optimized energy consumption and devices that are designed to encourage energy-friendly practices.
What’s more? Smart engines and automobiles can be optimized to reduce their carbon footprint and become energy-friendly. As evidenced by the Paris summit and the wildfires in 2020, the world is becoming ecologically conscious. IoT devices in 2021 will focus heavily on reduced emissions, lowering air and ocean pollution, and minimizing power expenditure.
Location Data
As COVID-19 limited human interaction, location-based services soared during the pandemic. Businesses started leveraging location data to offer curbside pickup, virtual queues, and check-ins for reservations to enhance the customer experience during the pandemic.
According to experts, the use of location data will continue to be crucial for customer service and convenience in 2021. As people prefer being safe even as the vaccines are being delivered, location data will allow businesses to cater to their customers without compromising on customer or employee safety.
Digital twins
IoT is being helmed as the perfect technology partner for creating digital twins in many industries. As IoT collects a large amount of data through physical devices, this data can be reinterpreted to create the perfect digital twins. Also, IoT can offer visibility into the full product life cycle and unfold deeper operational intelligence. Companies like Siemens are already leveraging technologies like AIoT to design and create digital twins for product design and production. Coupled with AI, IoT will be used more commonly for creating digital twins in 2021.
A technology as dynamic as IoT can be leveraged for almost any application. Therefore, it may surprise us all in the way it progresses in 2021. However, experts believe that the above 5 IoT industry trends will rule 2021 for sure.
Frequently Asked Questions
What are the latest IoT industry trends?
The use of IoT in Healthcare, Artificial Intelligence, workforce management, and ecological conservation can be deemed as some of the latest trends in IoT.
What is the future scope of IoT?
As experts believe there will be over 85 billion connected devices by the end of 2021, and the numbers are promising for upcoming years, we can safely say that the future of IoT is indeed bright.
What industries are most likely to use the Internet of things technology?
IoT is a dynamic technology with applications in almost every industry. However, industries like healthcare, construction, manufacturing, tech, and resource management are most like to use IoT right now.
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IoT Security
Article | June 27, 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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Industrial IoT, Theory and Strategy
Article | May 17, 2023
Explore the emerging complexities of IoT data governance with 7 key challenges to tackle. Address data privacy, security, and ethical concerns, empowering your business for success in 2023 and beyond.
Contents
1 The Case for Maintaining IoT Data Governance
2 Challenges of IoT Data Governance
2.1 Lack of Organizational Commitment
2.2 Data Privacy Concerns
2.3 Lack of Endpoint Security for IoT Devices
2.4 Issues with IoT Device Authentication
2.5 Increasing Volume of Unstructured Data
2.6 Unethical Use of IoT Data
2.7 Inadequate Data Governance Protocols
3 Addressing IoT Data Governance Challenges
3.1 Security by Design
3.2 Awareness Initiatives
3.3 Standardized Data Governance Policies
4 Conclusion
1 The Case for Maintaining IoT Data Governance
The growing use of IoT devices across various industries has caused a surge in data volume. Most of these devices store sensitive company data, which plays a crucial role in business operations but can have dire consequences if it falls into the wrong hands. Thus, companies need to understand what is IoT governance and its implementation to safeguard sensitive data from unauthorized access and malicious exploitation.
2 Top Challenges in IoT Data Governance for Businesses
2.1 Lack of Organizational Commitment
Organizational commitment is essential for effective IoT data governance. There needs to be a clear purpose and goals regarding data governance that are communicated to all stakeholders. Not focusing on organizational commitment can result in a lack of alignment between the organization's goals and the IoT data governance strategy, as well as uncertainty about ownership and accountability for data governance across the organization.
2.2 Data Privacy Concerns
Ensuring data privacy is a significant concern when implementing IoT data management to maintain IoT data governance security. With the vast amount of data generated by IoT devices, there is an increased risk of personal and sensitive data being compromised. Therefore, it is crucial to identify potential vulnerabilities, mitigate the risk of data privacy breaches in IoT environments, and anonymize user data for consumer devices.
2.3 Lack of Endpoint Security for IoT Devices
IoT devices are often designed with limited processing power and memory, and as such, many connected devices do not have built-in security features. This makes them attractive targets for hackers seeking to access confidential data or disrupt operations. Without proper endpoint security measures, IoT devices can be compromised, leading to data breaches, network downtime, and other security incidents that can compromise the entire system's integrity.
2.4 Issues with IoT Device Authentication
When IoT devices are designed without proper authentication mechanisms, it can be challenging to verify their identities. This results in possible unauthorized access, data breaches, and other security incidents. To supplement IoT data management practices, companies must implement secure authentication protocols specifically designed for IoT environments, such as device certificates, digital signatures, and multi-factor authentication, to maintain IoT data governance.
2.5 Increasing Volume of Unstructured Data
IoT devices generate vast amounts of data in various formats and structures, including text, images, audio, and video, which can be difficult to process, manage, and analyze. This data is often stored in different locations and formats, making it challenging to ensure quality and consistency. Moreover, this flood of unstructured data can contain sensitive information that must be protected to comply with regulations and standards. For effective IoT data governance, it is necessary to implement data classification, metadata management, and data quality management to make sense of unstructured data.
2.6 Unethical Use of IoT Data
IoT devices collect data that can be sensitive and personal, and misuse can lead to various negative consequences. Data from IoT devices can be used to develop insights, but it must be handled carefully to avoid privacy violations, discrimination, or other negative consequences. Ensuring data ethics requires organizations to consider the potential impacts of their data collection and use practices on various stakeholders. This involves addressing issues such as data privacy, data ownership, transparency, and bias in IoT data analytics.
2.7 Inadequate Data Governance Protocols
Without proper data governance protocols, IoT data may be inaccurate, incomplete, or difficult to access or analyze, reducing the effectiveness of IoT systems and limiting the potential benefits they can provide. Additionally, inadequate data governance protocols can lead to security and privacy vulnerabilities, potentially exposing sensitive data to unauthorized access or theft. This can result in legal and regulatory penalties, reputational damage, and a loss of customer trust.
3 Addressing IoT Data Governance Challenges
3.1 Security by Design
This approach involves integrating security and governance considerations into the design and development of IoT systems from the outset. This helps minimize vulnerabilities, prevent breaches that may compromise the confidentiality, integrity, and availability of IoT data, and help maintain IoT data governance. In addition, by prioritizing security in the design phase, organizations can implement security controls and features tailored to their IoT systems' specific needs, which can help prevent unauthorized access, manipulation, or theft of IoT data.
3.2 Awareness Initiatives
IoT data governance challenges can arise due to an improperly trained workforce that may not recognize the purpose and benefits of data governance practices. Awareness initiatives can help organizations develop a culture of security and privacy. These initiatives can educate employees and stakeholders about the risks and best practices associated with IoT data governance, including the importance of data security, privacy, and ethical considerations. By raising awareness of these issues, organizations can promote a culture of responsible data management, encourage stakeholders to adhere to data governance policies and procedures, and reduce the risk of human error or intentional misconduct that could compromise IoT data.
3.3 Standardized Data Governance Policies
Collaboration between local, regional, and federal governments and businesses is essential to establishing frameworks for implementing IoT and related technologies within their jurisdictions. Cooperation between governments and enterprises is crucial for implementing a standardized IoT data governance policy. This will protect end-users by mandating basic standards in procurement processes and creating regulations and guidelines that promote responsible data governance.
4 IoT Data Governance: Future Outlook
Data is one of the most valuable resources for organizations today, and addressing the problem of IoT data governance will ensure that the IoT of enterprises is used effectively and responsibly. Straits Research reported that the worldwide data governance market had a worth of USD 2.1 billion in 2021 and is projected to reach an estimated USD 11.68 billion by 2030. IoT devices are a key driving factor behind the growth of the data governance market, and as the amount of data generated and the number of devices grows, so will the complexity of data governance. By maintaining strong data governance policies and tracking changes in policies and best practices, businesses can ensure compliance and maintain trust in the long run.
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