IoT Security
Article | October 11, 2023
Explore the IoT certifications and grow your skills with the transforming landscape. Including Iot security certifications, this curated list will help you to boost career in the IoT industry.
As the Internet of Things continues to expand its reach across industries, the need for robust security measures to safeguard connected devices and data has become paramount. With IoT systems' growing complexity and interconnectivity, organizations seek professionals with specialized knowledge and expertise in IoT security. In response to this demand, various certifications have emerged to validate individuals' skills and provide them with a competitive edge in the IoT industry. In this article, we will explore some key IoT security certifications that can significantly enhance one's career prospects and contribute to IoT solutions' safe and secure deployment.
1. IoT Security Certification and Cybersecurity
Intertek’s IoT Security Certification and Cybersecurity provides IoT certification and testing services to validate the security of connected products. Securing endpoints and ecosystems has become crucial with the rapid growth of the Internet of Things. Intertek's total quality assurance approach involves understanding the product, use cases, integration with other systems, and developing a roadmap to ensure compliance with industry standards and regulations. Their IoT security and cybersecurity experts guide clients in choosing the most relevant program for their product and target markets, instilling confidence in product security. Intertek offers services such as the Cyber Assured Program, vulnerability assessments, penetration testing, testing to standards like ANSI/UL 2900 and IEC 62443, connected medical device security, industrial automated control systems security (IEC 62443), and advisory services. Intertek's expertise helps clients address cybersecurity risks and ensure the security of their IoT products.
2. Securing IoT - Build secure IoT solutions: 2-in-1
The Securing IoT: Build Secure IoT Solutions: 2-in-1 course is a comprehensive training program designed to help IoT product designers, IoT product managers, IT security professionals, and security engineers build secure and robust Internet of Things systems. The course consists of 'Fundamentals of IoT Security' and 'Security Engineering for the IoT.' The learners will delve into IoT security architectures, regulations, and standards. Privacy concerns and Privacy by Design principles and practical examples of conducting Privacy Impact Assessments are addressed. Cryptographic solutions, identity and access management, and key management solutions are explored, along with the cloud's secure connectivity, processing, and storage of data. By the end of the program, participants will have the skills to identify threats to their organization's data and IoT systems, employing design techniques, applied cryptography, and secure cloud connectivity for robust security.
3. IOT Security Professional (ICIP)
The IoT Security Professional (ICIP) program offered by ISAC is designed to provide participants with a comprehensive understanding of cyberattacks on IoT and SCADA systems. The training focuses on offensive testing techniques to better understand and combat hack and malware attacks. Participants will learn about discovering sensitive devices, network hacking via IoT, hacking smart devices, and controlling SCADA systems. The program includes case studies on malware like WannaCry and Crash Override and defensive measures like threat intelligence and endpoint protection. The course suits security researchers, forensic investigators, security teams, law enforcement agencies, and military personnel. Successful completion of the program grants a Clean Exit Professional Ethics Certification and inclusion in the National Security Database.
4. Internet of Things Security Expert Training
The Internet of Things Security Expert course offered by Cognixia is a comprehensive training program designed for professionals seeking to enhance their knowledge of IoT security. The course covers various IoT security platforms and provides hands-on training with relevant tools. It consists of three major modules: python, advanced IoT training and certification, and IoT Security. The Python module familiarizes candidates with the versatile programming language and its applications in IoT development. The Advanced IoT Training and Certification module covers IoT ecosystems' architecture, development, deployment, and security with real-life case studies. The IoT Security module focuses on securing IoT devices, covering architecture, practical attacks, vulnerability disclosure, and securing connected products. The course offers lifetime access to learning materials and round-the-clock technical support.
5. IOT Analyst Certification
One of the online IoT certification courses, the IT Analyst Certification is a 12-month program that focuses on combining IoT with Analytics to unlock valuable data from connected IoT devices. The course comprises three courses covering data acquisition, exploratory analysis, cleaning, and final analysis for IoT systems. It also teaches how advanced analytics and machine learning algorithms can be applied to build complex IoT solutions. The program is suitable for students from all backgrounds, and no prior knowledge of analytics or IoT is required, although basic quantitative skills are beneficial. After completing the curriculum and passing the certification test, students receive the IOT Analyst Certification, enabling them to process and analyze data from IoT sensors and become proficient in IoT analytics. The certification opens up opportunities in the fast-growing Big Data and Analytics industry, where IoT analytics is widely applied to predict future technology trends.
6. IOT Professional Certification
The IOT Professional Certification offered by Jigsaw Academy is a comprehensive program designed to help individuals master the implementation of IoT using Arduino. This 12-month online iot certification course uses the Arduino platform to build IoT solutions from scratch. The program consists of four courses covering various IoT aspects, including sensor-connected devices and gateways. Students will engage in hands-on exercises, real-life case studies, and a capstone project to apply their knowledge effectively. Upon completion, students receive a certification that validates their skills in building and applying IoT solutions, setting up IoT Cloud for data storage and analysis, and proficiency in Arduino programming language. The IOT Professional Certification equips individuals with the necessary skills and knowledge to excel in the high-demand field of IoT and opens up better job prospects.
7. IoT and its Applications
TCS iON Digital Learning Hub offers the 'IoT and its Applications' certificate course, providing learners with a comprehensive understanding of the fundamentals of the Internet of Things. The course spans 5 to 6 months, delivered in English through digital lectures, e-learning resources, and community-based virtual classrooms. Through industry assignments and expert-led instruction, participants gain theoretical and practical insights into IoT applications. Upon completion, learners receive a verifiable digital certificate and gain industry-level skills required for test engineers or computer programmers. This course helps learners grasp IoT theories and practical applications, offering valuable career opportunities.
Conclusion
In an era where the Internet of Things is transforming industries and revolutionizing the way, we interact with technology, ensuring the security of IoT systems has become a critical imperative. The certifications discussed in this article represent a selection of key credentials available to professionals seeking to boost their careers in the IoT industry. By obtaining these certifications, individuals can validate their expertise in IoT security, demonstrating their commitment to upholding best practices and safeguarding the integrity of connected devices and data.
As the demand for IoT security professionals continues to rise, these certifications will serve as powerful assets, opening doors to exciting opportunities and positioning individuals as trusted experts in the ever-evolving field of IoT security. By investing in these certifications, professionals can take significant strides toward advancing their careers and contributing to the secure and responsible growth of the IoT ecosystem.
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IoT Security
Article | June 28, 2023
Building resilient IoT networks: Exploring the top technologies for enhancing IoT security and protecting as well as safeguarding against evolving cyber threats in the interconnected era of Industry 4.0.
Contents
1. What is Network Resilience and Why is it Needed?
1.1 Continuous Operation
1.2 Mitigating Security Threats
1.3 Data Protection
1.4 System Availability
1.5 Risk Management
1.6 Regulatory Compliance
2. Factors to Consider for Network Resilience
3. Top Trends in IoT Security
3.1 Zero Trust and AI
3.2 Supply Chain Security
3.3 Network Segmentation and Segregation
3.4 Over-the-Air (OTA) Updates
3.5 Device Authentication and Authorization
3.6 Software-defined Networking (SDN) Security
3.7 Identity and Access Management (IAM)
4. Conclusion
1. What is Network Resilience and Why is it Needed?
Network resilience refers to the ability of an IoT network to withstand and recover from disruptions, attacks, or failures while maintaining its essential functions. It involves implementing measures to ensure the network remains available, reliable, and secure, even during security threats or unexpected events.
Ensuring network resilience is a critical aspect of IoT network security. Network resilience refers to the ability of an IoT network to withstand and recover from disruptions, attacks, or failures while maintaining its essential functions. Ensuring network resilience in IoT network security is crucial for the following reasons:
1.1 Continuous Operation
IoT networks often support critical applications and services that require uninterrupted operation. Network resilience ensures that these applications can continue functioning even during disruptions, such as network failures or security incidents. It minimizes downtime and ensures business continuity.
1.2 Mitigating Security Threats
IoT networks are susceptible to various cybersecurity threats, including malware, unauthorized access, or Distributed Denial of Service (DDoS) attacks. Network resilience measures help mitigate these threats by implementing security controls, monitoring network traffic, and enabling prompt detection and response to security incidents.
1.3 Data Protection
IoT devices generate and transmit vast amounts of sensitive data. Network resilience safeguards data integrity, confidentiality, and availability by implementing secure communication protocols, encryption mechanisms, and access controls. It ensures that data remains protected even during network disruptions or security breaches.
1.4 System Availability
IoT systems often rely on real-time data processing and communication. Network resilience ensures that data flows seamlessly, allowing IoT devices to exchange information and execute tasks without interruptions. It supports critical functions such as monitoring, control, and decision-making processes.
1.5 Risk Management
Building network resilience helps organizations effectively manage risks associated with IoT deployments. By identifying vulnerabilities, implementing protective measures, and having response plans in place, organizations can minimize the impact of security incidents, reduce financial losses, and maintain the trust of stakeholders.
1.6 Regulatory Compliance
Many industries have specific regulations and standards governing the security and resilience of IoT networks. By ensuring network resilience, organizations can demonstrate compliance with these requirements, avoiding penalties, legal issues, and reputational damage.
2. Factors to Consider for Network Resilience
Implementing redundancy and failover mechanisms within the network infrastructure helps mitigate the impact of single points of failure. This involves deploying backup systems, redundant network paths, and failover mechanisms to ensure continuous operation despite a failure or attack. Traffic Monitoring and Anomaly Detection for Continuous network traffic monitoring helps identify abnormal patterns or behaviours that may indicate security threats or attacks. By leveraging intrusion detection and prevention systems (IDPS) and traffic analysis tools, organizations can promptly detect and respond to network anomalies, safeguarding network resilience. Moreover, segmentation and Isolation: Dividing the IoT network into segments or zones and isolating critical devices or systems from less secure ones enhances network resilience. Implementing proper network segmentation, VLANs (Virtual Local Area Networks), or software-defined networking (SDN) enables effective control, containment, and mitigation of security incidents.
DDoS attacks significantly threaten network resilience by overwhelming the network's resources and causing service disruption. Deploying robust DDoS protection measures, such as traffic filtering, rate limiting, and traffic diversion, helps mitigate the impact of such attacks and ensures network availability. Incident Response and Establishing comprehensive incident response and recovery plans specific to IoT network security incidents is crucial. These plans should outline clear procedures, roles, and responsibilities to efficiently respond to and recover from security breaches or disruptions, minimizing downtime and maintaining network resilience. In addition, regular penetration testing, vulnerability assessments, and network audits help identify weaknesses and vulnerabilities in the IoT network infrastructure. Promptly addressing these issues through patches, updates, and security configuration adjustments strengthens network resilience by proactively addressing potential security risks.
By implementing these measures, organizations can enhance the resilience of their IoT networks, ensuring continuous operation, prompt threat detection, and effective response to security incidents. Network resilience plays a vital role in maintaining IoT systems' integrity, availability, and reliability in the face of evolving security challenges.
3. Top Trends in IoT Security
3.1 Zero Trust and AI
Zero Trust is an emerging security concept that assumes no implicit trust towards devices or users, even if they are already inside the network perimeter. Implementing Zero Trust principles in IoT networks can help mitigate the risks associated with compromised devices and unauthorized access for IoT security. In order to bolster cybersecurity measures, adopting a zero trust approach. Effectively addressing cybersecurity challenges entails not merely technological solutions but a comprehensive organizational strategy rooted in cultural and policy frameworks. Emphasizing the zero trust concept underscores the importance of policy implementation throughout the entire organization, complementing technological measures.
3.2 Supply Chain Security
The complex and interconnected nature of IoT supply chains introduces security risks. The supply chain for IoT devices involves multiple stages, including device manufacturing, software development, distribution, and deployment. Each stage presents potential security risks that can compromise the integrity and security of the IoT network. This includes adopting secure supply chain management practices, such as verifying the security practices of suppliers and manufacturers, and establishing clear security requirements and standards for the entire supply chain. Conducting third-party risk assessments helps evaluate the security posture of suppliers and vendors to identify any potential vulnerabilities or weaknesses.
3.3 Network Segmentation and Segregation
In IoT security, minimizing the potential impact of a compromised IoT device is crucial, and network segmentation and segregation play a vital role in achieving this goal. Network segmentation involves dividing the network into separate zones or segments, based on factors such as device type, functionality, or security requirements. The containment strategy helps minimize the impact of a security breach by isolating compromised devices and preventing lateral movement within the network.
3.4 Over-the-Air (OTA) Updates
Software updates play a critical role in maintaining the integrity and security of IoT devices. IoT devices frequently require updates to address software bugs, patch vulnerabilities, or introduce new features. Over-the-Air (OTA) update mechanisms are being enhanced with robust security measures to ensure the secure delivery and installation of updates. Code signing is a prevalent practice where updates are digitally signed with cryptographic keys to verify the authenticity and integrity of the software. Secure boot is another important mechanism that establishes a chain of trust during the device boot-up process, ensuring that only authorized and tamper-free software is loaded onto the device.
3.5 Device Authentication and Authorization
The increasing number of IoT devices poses a significant challenge in ensuring secure and trusted authentication and authorization. Two-factor authentication (2FA), for example, adds an extra layer of protection by requiring users or devices to provide two separate forms of authentication, such as a password and a unique code sent to a mobile device. Digital certificates, on the other hand, enable secure and trusted device authentication by leveraging public key infrastructure (PKI) technology. Each IoT device is issued a unique digital certificate, which serves as a digital identity, allowing for secure communication and verification of device authenticity.
3.6 Software-defined Networking (SDN) Security
Securing Software-defined Networking (SDN) environments is paramount to protect IoT deployments. SDN offers centralized control and management of network resources, providing flexibility and scalability. This ensures that only authorized entities can access and make changes to the SDN infrastructure, preventing unauthorized access and configuration changes. Additionally, continuous traffic monitoring and analysis enable the detection of suspicious activities and potential security breaches. Encryption IoT standards and protocols should be employed to secure communication between the SDN controller, switches, and IoT devices, safeguarding data privacy and integrity. Network segmentation within the SDN environment helps limit the impact of security breaches, reducing the attack surface.
3.7 Identity and Access Management (IAM)
Implementing IAM solutions, such as role-based access control (RBAC) and multi-factor authentication (MFA), within IoT networks significantly enhances network security. IAM ensures that only authorized individuals can access and interact with IoT devices and systems. RBAC enables administrators to assign specific access privileges based on user roles and responsibilities, reducing the risk of unauthorized access. Additionally, incorporating MFA adds an extra layer of security by requiring users to provide multiple forms of authentication, such as a password and a unique token or biometric verification. This significantly reduces the risk of unauthorized access even if a user's credentials are compromised.
4. Conclusion
The technologies discussed in this article play a crucial role in enhancing IoT network security and resilience. By leveraging these technologies, organizations can mitigate the risks associated with IoT deployments, protect against cyber threats, and ensure the reliability and continuity of their IoT networks. As the IoT landscape evolves, staying up-to-date with these top technologies will be essential for organizations to maintain a robust and secure IoT infrastructure.
The transformative landscape of Industry 4.0 demands strong network security in IoT environments. The top technologies discussed in this article empower organizations to enhance network resilience, protect against cyber threats, and ensure the uninterrupted functioning of IoT networks. Embracing these technologies and staying ahead of emerging threats, helps organizations build a secure foundation for their IoT deployments and capitalize on the vast opportunities offered by the IoT ecosystem.
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Enterprise Iot
Article | May 11, 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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Enterprise Iot
Article | July 11, 2022
Artificial intelligence is becoming increasingly crucial in IoT applications and deployments. Over the past two years, investments and acquisitions in firms that combine AI and IoT have increased. IoT platform software from top suppliers now includes integrated AI features, including machine learning-based analytics.
When artificial intelligence is linked with the internet of things, we get Artificial Intelligence of Things (AIoT). The prime motive for combining AI and IoT is that, while IoT devices are used to gather data and send it to a cloud or other location where it can be stored using the internet, AI, which is regarded as the brain of AIoT, is what actually aids in decision-making and simulates how machines would act or react.
Other artificial intelligence (AI) tools, such as speech recognition and computer vision, can assist reveal patterns in data that previously needed human evaluation.
AI applications for IoT-enabled companies help them avoid several issues:
Preventing expensive unplanned downtime
Predictive maintenance can lessen the adverse economic effects of unplanned downtime by employing analytics to anticipate equipment failure and arrange orderly maintenance processes. In order to predict equipment failure, machine learning enables the discovery of patterns in the continuous streams of data produced by today's technology.
Operational efficiency advancement
IoT with AI capabilities can also increase operational effectiveness. By processing continuous data streams to find patterns invisible to the human eye and not visible on simple gauges, machine learning can predict operating conditions and identify parameters that need to be adjusted immediately to maintain ideal results, just as it can predict equipment failure.
Improved risk management
IoT and AI-powered applications enable businesses to automate for quick reaction, better analyze and predict a range of hazards, and control worker safety, financial loss, and cyber threats.
Finding an IoT system that does not incorporate AI could soon be uncommon. With the help of AI, organizations can truly enhance the potential IoT and effectively put it into use for improving the overall functioning.
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