SCADA Market Size Global SCADA Market size was USD 12.02 billion in 2025 and is projected to reach USD 12.8 billion in 2026 and USD 13.63 billion in 2027, growing further to USD 22.56 billion by 2035, showing a steady growth rate of 6.5%. Around 68% of industries are adopting SCADA systems for real-time monitoring and control. Nearly 64% of energy and utility sectors rely on SCADA for efficient operations, while about 61% of manufacturing units use it to improve productivity and reduce downtime. The US SCADA Market is showing strong growth due to rising automation demand. Around 71% of industrial companies in the US use SCADA systems for monitoring and control. Nearly 66% of energy utilities depend on SCADA for grid management and fault detection. About 59% of manufacturing facilities are using SCADA to improve efficiency and reduce operational risks. In addition, close to 54% of companies are investing in advanced SCADA solutions with cloud and IoT integration, supporting further market expansion. Key Findings - Market Size: Global SCADA Market reached $12.02 billion in 2025, $12.8 billion in 2026, and will hit $22.56 billion by 2035, growing at 6.5%. - Growth Drivers: Around 68% demand automation, 64% energy monitoring, 61% manufacturing efficiency, 58% smart systems, and 55% industries adopt real-time solutions. - Trends: About 65% cloud adoption, 62% IoT integration, 59% analytics usage, 57% remote monitoring, and 54% focus on cybersecurity systems. - Key Players: Schneider Electric SE (France), Siemens AG (Germany), ABB (Switzerland), Honeywell International Inc. (US), Rockwell Automation Inc. (US) & more. - Regional Insights: North America holds 32%, Europe 27%, Asia-Pacific 29%, and Middle East & Africa 12%, showing balanced industrial automation growth. - Challenges: Around 60% face cybersecurity risks, 55% system complexity issues, 52% integration challenges, 49% skilled workforce gaps, and 47% maintenance concerns. -
Apr 8, 2026 · via globalgrowthinsights.com
Cybersecurity researchers have lifted the curtain on a stealthy botnet that's designed for distributed denial-of-service (DDoS) attacks. Called Masjesu, the botnet has been advertised via Telegram as a DDoS-for-hire service since it first surfaced in 2023. It's capable of targeting a wide range of IoT devices, such as routers and gateways, spanning multiple architectures. "Built for persistence and low visibility, Masjesu favors careful, low-key execution over widespread infection, deliberately avoiding blocklisted IP ranges such as those belonging to the Department of Defense (DoD) to ensure long-term survival," Trellix security researcher Mohideen Abdul Khader F said in a Tuesday report. It's worth noting that the commercial offering also goes by the moniker XorBot owing to its use of XOR-based encryption to conceal strings, configurations, and payload data. It was first documented by Chinese security vendor NSFOCUS in December 2023, linking it to an operator named "synmaestro." A subsequent iteration of the botnet observed a year later was found to have added 12 different command injection and code execution exploits to target routers, cameras, DVRs, and NVRs from D-Link, Eir, GPON, Huawei, Intelbras, MVPower, NETGEAR, TP-Link, and Vacron, and obtain initial access. Also added were new modules to conduct DDoS flood attacks. "As an emerging botnet family, XorBot is showing a strong growth momentum, continuously infiltrating and controlling new IoT devices," NSFOCUS said in November 2024. "Notably, these controllers are increasingly inclined to use social media platforms such as Telegram as the main channels for recruitment and promotion, attracting target 'customers' through initial active promotional activities, laying a solid foundation for the subsequent expansion and development of the botnet." The latest findings from Trellix show that Masjesu has marketed the ability to carry out volumetric DDoS attacks, emphasizing its diverse botnet infrastructure and its suitability for targeting content delivery networks (CDNs), game
Apr 8, 2026 · via thehackernews.com
Cybersecurity Leaders to Watch in California’s High-Tech Manufacturing Industry California’s high-tech manufacturing sector sits at the intersection of advanced hardware, connected products, cloud infrastructure, medical devices, and industrial-scale research and development. That makes cybersecurity a cross-functional discipline rather than a siloed one. The leaders in this feature reflect that reality. Their backgrounds span artificial intelligence security, cloud security, product security, compliance, risk management, secure engineering, and the protection of complex manufacturing and healthcare-adjacent environments. Kshitish Soman — Head of Information Security, Seagate Technology At Seagate Technology, Kshitish Soman serves as head of information security, with responsibility spanning artificial intelligence security, risk management, cloud security, and security architecture. His role builds on an unusual mix of product, engineering, and security leadership. Before moving into Seagate’s information security organization, he led engineering and later products, engineering, and operations for Lyve Cloud, giving him direct experience in the technical and operational environments that security teams are often asked to protect. Earlier in his career, Soman co-founded OmegaTrace, an IoT product engineering company focused on indoor location sensing and tracking, and also co-founded Digigel, a scalable IoT and fog computing platform. Previous leadership roles at KPMG, Pali Capital, Marsh, Aon, American Express, and other firms added experience in consulting, enterprise architecture, systems design, and large-scale software delivery. That blend of engineering depth and security leadership is especially relevant in high-tech manufacturing environments where cloud platforms, connected systems, and operational resilience increasingly overlap. Naor Penso — Chief Information Security Officer, Cerebras Systems Naor Penso is chief information security officer at Cerebras Systems, where he oversees security at a company building large-scale artificial intelligence computing infrastructure. Before joining Cerebras, he served as vice president and head of product security at FICO, following earlier leadership positions including chief technology officer for cybersecurity at Amdocs and chief information
Apr 8, 2026 · via securityboulevard.com
Cybersecurity in the Age of Instant Software AI is rapidly changing how software is written, deployed, and used. Trends point to a future where AIs can write custom software quickly and easily: “instant software.” Taken to an extreme, it might become easier for a user to have an AI write an application on demand—a spreadsheet, for example—and delete it when you’re done using it than to buy one commercially. Future systems could include a mix: both traditional long-term software and ephemeral instant software that is constantly being written, deployed, modified, and deleted. AI is changing cybersecurity as well. In particular, AI systems are getting better at finding and patching vulnerabilities in code. This has implications for both attackers and defenders, depending on the ways this and related technologies improve. In this essay, I want to take an optimistic view of AI’s progress, and to speculate what AI-dominated cybersecurity in an age of instant software might look like. There are a number of unknowns that will factor into how the arms race between attacker and defender might play out. How flaw discovery might work On the attacker side, the ability of AIs to automatically find and exploit vulnerabilities has increased dramatically over the past few months. We are already seeing both government and criminal hackers using AI to attack systems. The exploitation part is critical here, because it gives an unsophisticated attacker capabilities far beyond their understanding. As AIs get better, expect more attackers to automate their attacks using AI. And as individuals and organizations can increasingly run powerful AI models locally, AI companies monitoring and disrupting malicious AI use will become increasingly irrelevant. Expect open-source software, including open-source libraries incorporated in proprietary software, to be the most targeted, because vulnerabilities are easier to find in source code. Unknown No. 1
Apr 7, 2026 · via schneier.com
Abstract The Internet of Things (IoT) presents considerable hurdles, especially in maintaining security across its swiftly proliferating applications. Administering security protocols and updating individual IoT devices to address emerging risks is resource intensive. Furthermore, the extensive data produced by IoT devices presents a significant opportunity for machine learning to improve threat detection. This study investigates the application of deep learning frameworks for the analysis of IoT network traffic to enhance intrusion detection and strengthen cybersecurity. A hybrid intrusion detection system (HIDS) is suggested, utilizing an iterative ensemble method that combines Convolutional Neural Networks (CNN) and Long Short-Term Memory (LSTM) networks for enhanced classification accuracy. Adaptive Synthetic Sampling (ADASYN) is utilized to rectify data imbalance, whereas Recursive Feature Elimination (RFE) enhances classifier efficacy by eliminating extraneous features. This comprehensive approach improves detection precision and system robustness against cyber-attacks. The proposed CNN–LSTM-based IDS was evaluated on five benchmark datasets. Across these datasets, the model consistently achieved high performance, including 98.89% accuracy on KDDCup99, 97% on CAN-BUS, 97% on NSL-KDD, and 99% on CICIDS, demonstrating its robustness across diverse IoT-Fog scenarios. Although increasing the model complexity yielded only marginal gains in detection performance, it substantially increased computational demands, indicating diminishing returns from more complex architectures. Customized deep learning approaches combined with effective preprocessing significantly improved IDS performance in IoT-Fog cybersecurity frameworks. Data availability The datasets used and/or analyzed during the current study available from the corresponding author on reasonable request. References Thakkar, A. & Lohiya, R. A survey on intrusion detection system: feature selection, model, performance measures, application perspective, challenges, and future research directions. Artif. Intell. Rev. 55(1), 453–563 (2022). Liu, Y., Dong, X., Zio, E. & Cui, Y. Active Resilient Secure Control for Heterogeneous Swarm Systems Under Malicious Cyber-Attacks. IEEE Trans. Syst. Man Cybernetics: Syst. 25, 1–10. https://doi.org/10.1109/TSMC.2025.3580940 (2025). Yi, L., Yin,
Apr 7, 2026 · via nature.com
Digital Power Utility Market Size, Share, Growth, and Industry Analysis, By Type (Hardware Service, software Service), By Application (Power Generation, Transmission and Distribution, Energy Storage, Other), Regional Insights and Forecast to 2035 Digital Power Utility Market Overview The Digital Power Utility Market size valued at USD 8447.48 million in 2026 and is expected to reach USD 17909.59 million by 2035, growing at a CAGR of 9% from 2026 to 2035. The Digital Power Utility Market is undergoing rapid transformation driven by the integration of smart technologies, with over 68% of global utilities implementing digital grid solutions and approximately 72% deploying advanced metering infrastructure (AMI) across operations. Around 65% of utilities worldwide have adopted cloud-based asset management systems, while 58% utilize AI-driven predictive analytics to enhance grid efficiency. The Digital Power Utility Market Size is influenced by the increasing penetration of renewable energy, which accounts for nearly 30% of total global power generation capacity. Additionally, over 75% of utilities have initiated digital transformation roadmaps, highlighting strong Digital Power Utility Market Growth and Digital Power Utility Market Trends. In the United States, the Digital Power Utility Market Analysis shows that nearly 85% of utilities have installed smart meters, covering more than 120 million endpoints. Approximately 70% of utilities use real-time grid monitoring systems, while 62% rely on automated outage management platforms. Renewable integration has reached 40% of total installed capacity, increasing the demand for digital control systems. Around 55% of U.S. utilities utilize IoT-enabled devices, and 67% deploy cybersecurity frameworks to protect grid infrastructure. The Digital Power Utility Market Outlook in the U.S. is supported by over 50% adoption of distributed energy resource management systems (DERMS). Key Findings - Market Size: 68% utilities digitized, 72% smart meters deployed, 65% cloud adoption. - Growth Drivers: 78% smart grid adoption, 70% renewable integration, 68%
Apr 7, 2026 · via marketgrowthreports.com
Industrial systems are entering a new phase where data, connectivity, and automation converge at scale. The concept of Smart Manufacturing sits at the intersection of these forces, reshaping how factories operate, how assets are managed, and how decisions are made across production environments. For IoT decision makers and industrial leaders, Smart Manufacturing is not a single technology but an architectural shift. It combines connected devices, real-time data processing, and advanced analytics to create more adaptive, efficient, and resilient operations. Understanding how these systems work—and where their limits lie—is now critical for long-term competitiveness. Key Takeaways - Smart Manufacturing integrates IoT, data analytics, and automation to enable real-time visibility and control across industrial operations. - Edge computing, industrial connectivity, and interoperability standards are essential to support scalable deployments. - Use cases range from predictive maintenance to digital twins and supply chain optimization. - Benefits include improved efficiency and reduced downtime, but challenges remain around integration, cybersecurity, and legacy systems. - The ecosystem involves a complex mix of hardware vendors, connectivity providers, and industrial software platforms. What is Smart Manufacturing? Smart Manufacturing refers to the use of connected systems, sensors, and data-driven technologies to monitor, analyze, and optimize industrial production processes in real time. It leverages IoT infrastructure to create a digitally integrated environment where machines, systems, and operators can exchange data and coordinate actions. Within the broader IoT ecosystem, Smart Manufacturing represents one of the most mature and impactful domains of industrial IoT. It extends traditional automation by introducing connectivity and intelligence at every level—from shop floor equipment to enterprise systems—enabling continuous optimization rather than static control. Unlike conventional manufacturing systems that rely on periodic monitoring and manual intervention, Smart Manufacturing systems are designed to be adaptive. They can detect anomalies, trigger automated responses, and support predictive decision-making based on continuous
Apr 7, 2026 · via iotbusinessnews.com
The Critical Role of IoT in Emergency Rooms Zac AmosZac Amos Emergency rooms (ERs) operate in high-stakes environments where rapid decision-making directly impacts patient outcomes. Internet of Things (IoT) technology integrates connected devices into these settings, providing real-time data streams that enhance operational efficiency, patient monitoring, and resource management. These advancements offer transformative potential in health care delivery. IoT wearables and sensors continuously track vital signs like heart rate, blood pressure, and respiratory patterns. These devices send alerts to medical staff if a patient’s condition deteriorates, allowing quick interventions that can save lives. In busy ERs, this reduces manual checks and catches issues early. For example, connected ECG monitors and pulse oximeters provide instant data to dashboards accessible on tablets or smartphones. Nurses then no longer need to perform frequent checks, freeing them for direct care. This setup could prove especially vital during mass-casualty events or surges, such as flu seasons. When integrated with AI, IoT systems could analyze trends to predict complications like sepsis. ERs may waste time searching for defibrillators, ventilators, or infusion pumps amid chaos. IoT tags with RFID or Bluetooth enable real-time location systems to pinpoint equipment instantly. This visibility cuts delays during crises and optimizes inventory. Maintenance is proactive, too. IoT sensors can detect wear on pumps or batteries, alerting staff of necessary maintenance before failures occur. ER overcrowding leads to hallway waits and delayed care, straining resources. IoT sensors on beds monitor occupancy and turnover readiness, providing live dashboards for administrators. These systems can forecast demand using historical data and current inflows to enable streamlined intake. Demand forecasting ranges from simple models to advanced algorithms that incorporate patient volume, number of available beds, average length of stay, equipment use, disease trends, and staff availability. Effective solutions leverage this data to plan resources across shifts
Apr 6, 2026 · via iotforall.com
AI is becoming both a threat and a tool in smartphone security. As phishing attacks grow more sophisticated, vendors are increasing their focus on on-device AI protections. This blog explores what that means for the future of smartphone security. AI-generated phishing attacks pose a big threat to consumers and businesses if device vendors don’t fight back with more sophisticated on-device natural language checks and deepfake detectors. According to the latest findings in Omdia’s Mobile Device Security Scorecard, phishing attacks continue to be the most common smartphone security threat to consumers. Yet, hands-on testing of the latest devices, including the iPhone 17 Pro Max, showed that no device could detect and stop the kinds of sophisticated, hand-made phishing attempts which AI will make more common. 27% of consumers reported experiencing phishing scams in the past year - according to the Omdia Mobile Device Security Survey conducted in October 2025 - making it the most common type of security incident on smartphones. The survey also showed that phishing attacks are most common in English-speaking countries, with the United States leading with 40% of respondents experiencing phishing attacks, followed by the United Kingdom (36%), Ireland (35%), Canada (32%), and Australia (30%). Singapore, where English is one of the official languages, also reported a high rate of 26%. This trend suggests that scammers prioritise targeting English-speakers, likely due to the language's global prevalence, with a particular focus on high-income consumers in mature markets. The threat that AI poses to smartphone security As more advanced AI and larger LLM models become more accessible and affordable, scammers will have more tools in their belt. They can craft more sophisticated scam campaigns quicker than ever before, and can even tailor it to each target with a greater understanding of more believable language and formatting - within Omdia’s
Apr 6, 2026 · via omdia.tech.informa.com
ACS Technologies Partners UAE's Tahaluf Al Emarat for India AI and IoT Expansion Partnership Announcement Details ACS Technologies officially announced its exclusive strategic partnership with UAE's Tahaluf Al Emarat on April 4, 2026. This follows earlier communications to the BSE on March 30 and March 31, 2026. The agreement designates ACS Technologies as Tahaluf's sole reseller for AI and IoT solutions across India. This pact is set to introduce Tahaluf's innovations into India's government, defence, and enterprise sectors. Strategic Value for ACS Technologies This partnership enables ACS Technologies to significantly expand its service portfolio with advanced AI and IoT capabilities. The company gains access to technologies such as smart city platforms, AI analytics, computer vision, and IoT asset tracking. ACS intends to use this alliance to strengthen its position in India's fast-growing AI-driven infrastructure market. Background on Partners ACS Technologies has experience with digital transformation projects for Indian government entities. In the last two years, the company has actively sought to expand its digital offerings and form alliances to boost its AI and IoT capabilities. Tahaluf Al Emarat is known in the Middle East for its expertise in AI, IoT, and cybersecurity, with past success in government and defence projects across the MENA region. New Capabilities and Focus ACS Technologies will now offer Tahaluf's full suite of AI and IoT products and services in India. The partnership specifically targets the government, defence, and large enterprise sectors, key areas for advanced technology adoption. ACS aims to enhance its market position in India's AI infrastructure development by providing a complete service model, including implementation of these solutions. Key Challenges to Monitor The success of this partnership will depend on ACS's ability to effectively integrate and market Tahaluf's solutions within India's competitive landscape. Relying on a single international partner for key technologies could
Apr 4, 2026 · via whalesbook.com
03 Apr AI CYBERSECURITY KEYNOTE SPEAKER & IT FUTURIST CONSULTING EXPERT FOR EVENTS Famous AI cybersecurity keynote speakers focus on the evolving trends that are transforming the way organizations protect their digital assets, networks, and data through artificial intelligence. Breakouts and training workshops by the world’s best AI cybersecurity keynote speakers help defense leaders, IT teams, and executives understand how AI can enhance threat detection, automate responses, and build resilient strategies in an increasingly demanding digital world. A major trend folks look at is threat detection and anomaly monitoring. Machine learning algorithms can analyze vast amounts of network traffic, system logs, and user behavior to identify suspicious activity in real time. Companies like CrowdStrike and Palo Alto Networks get featured across celebrity AI cybersecurity keynote speakers talks for implementing AI systems that detect malware, ransomware, and phishing attacks faster than traditional security tools. Then thought leaders and futurist consultants also look at predictive capabilities. Automation, ML and LLM models can anticipate potential vulnerabilities, forecast attack patterns, and identify high-risk assets, allowing organizations to proactively mitigate threats rather than react to breaches. This approach top AI cybersecurity keynote speakers say reduces downtime, financial loss, and reputational damage. Automated incident response and remediation is also of note. Smart platforms can isolate compromised systems, deploy patches, and alert security teams automatically, minimizing the impact of attacks and accelerating recovery. This enables organizations futurist AI cybersecurity keynote speakers assert to respond faster to evolving threats while freeing human analysts to focus on strategic initiatives. SMEs and KOLs also identity and access management (IAM). Tech tools continuously monitor login activity, detect anomalies, and enforce adaptive authentication to prevent account takeovers and insider threats. Cloud security and IoT protection is an emerging trend. Like global AI cybersecurity keynote speakers posit, IT helps safeguard cloud-based systems and
Apr 3, 2026 · via futuristsspeakers.com
Manufacturing Cybersecurity Market Growth: Trends & Forecast to 2030 The global Manufacturing Cybersecurity Market is on a strong growth trajectory, expected to expand from USD 10.97 billion in 2025 to USD 17.39 billion by 2030, registering a CAGR of 9.7% during the forecast period. As manufacturing ecosystems become increasingly digital and interconnected, the need for robust cybersecurity frameworks is more critical than ever. With over 100 pages of detailed analysis, including 50+ tables and 10+ figures, the report provides deep insights into market trends segmented by solution, service type, security layer, and manufacturing verticals. Get More Info, Download Pdf Brochure: https://www.marketsandmarkets.com/pdfdownloadNew.asp?id=79811917 Rising Industry 4.0 Adoption Expands Cyber Risk Landscape The rapid adoption of Industry 4.0 and the Industrial Internet of Things (IIoT) is transforming manufacturing operations by connecting machines, systems, and supply chains. However, this growing connectivity significantly increases the cyberattack surface. To mitigate these risks, manufacturers are investing in advanced cybersecurity solutions that enable: - Real-time threat monitoring - Protection of interconnected industrial assets - Secure data exchange across systems Additionally, evolving regulatory frameworks focused on critical infrastructure protection, data privacy, and operational safety are compelling organizations to adopt integrated and compliant cybersecurity strategies. Endpoint & IoT Security Emerging as the Fastest-Growing Segment Among security types, endpoint and IoT security is projected to witness the highest growth rate over the forecast period. This surge is primarily driven by the rapid proliferation of connected devices across industrial environments. A significant number of IoT devices remain unmanaged, creating visibility gaps and security vulnerabilities. Cybersecurity firms highlight that endpoints often act as entry points for ransomware attacks, allowing attackers to infiltrate critical operational systems. As manufacturers deploy technologies such as: - Smart sensors - Robotics - Edge computing the number of endpoints continues to grow, increasing the demand for: - Endpoint Detection
Apr 3, 2026 · via marketsandmarkets.com
On March 28, the Gia Lai Investment Promotion Conference 2026 was held as a key event within the National Tourism Year – Gia Lai 2026 opening week. Speaking at the event, Binh outlined a vision to turn Gia Lai into an artificial intelligence hub, noting that AI is reshaping how economies, education systems, and societies operate. The question is no longer whether to adopt AI, but who will master it and who will be left behind. Every individual needs to use AI to boost productivity. He emphasized the need to integrate AI into curricula at all levels, from primary to higher education, with the dual approach of teaching AI itself and using AI as a learning tool. The goal is to cultivate a workforce capable of mastering advanced technologies in the future. For Gia Lai, he expressed the ambition not only to train talent but also to attract experts from both Vietnam and abroad. He said that FPT will accompany the province in developing key technology pillars, positioning Gia Lai as a pioneering center in the AI-driven development wave. “FPT commits to working alongside Gia Lai to develop strategic pillars in a way that reflects the province’s unique strengths. Gia Lai should not only serve itself but also create value for Vietnam and the world,” he said. As part of the event, FPT signed a cooperation agreement with the Gia Lai People’s Committee to promote breakthroughs in science, technology, innovation, and digital transformation for the 2026–2030 period. The company will participate in research, consulting, and implementation of technology and innovation initiatives in the province. Key technology areas identified for collaboration include AI, semiconductors, data, IoT, cybersecurity, quantum technology, robotics, and autonomous systems, as well as technologies supporting energy, environment, and digital transformation. The two sides also signed a memorandum of
Apr 3, 2026 · via vietnamnet.vn
When Your Own Eyes Turn Against You: How Compromised Security Cameras and IoT/OT Devices Become Tools for Your Attackers TL;DR Security cameras, IoT, and OT devices that are meant to protect us, are easily compromised and turned against defenders, enabling nation-state reconnaissance (Iranian hacks on Hikvision/Dahua cameras during strikes, Russian webcam abuse in Ukraine), espionage via exposed live feeds, ransomware pivots (Akira group bypassing EDR), massive botnets (Mirai/Eleven11bot), and physical disruption. Structural weaknesses like default credentials, poor patching, internet exposure, supply-chain risks and espionage by design makes them ideal attacker tools, especially since they can’t receive endpoint security agents. Zero Trust Connectivity (ZTc) solves this by enforcing network-level Zero Trust: it blocks unauthorized connections before they form, requires no endpoint agents, prevents lateral movement, and supports decentralized deployment with sovereign data custody — giving defenders a powerful way to secure all devices without traditional detection or centralized decryption. In short, the watcher must be properly isolated at the network layer. In cybersecurity, the watcher must be watched most closely of all. When Your Own Eyes Turn Against You: How Compromised Security Cameras and IoT/OT Devices Become Tools for Your Attackers Turning Defense Technology Against the Defenders We live in an era where security cameras, smart sensors, industrial controllers, other Internet of Things (IoT) and Operational Technology (OT) devices are deployed everywhere—from traffic poles, corporate boardrooms and factory floors to homes and critical infrastructure. They are meant to watch, alert, and protect. Yet when attackers gain control, these very devices become potent weapons in their hands: silent observers feeding real-time intelligence, hidden pivots into protected networks, launchpads for massive distributed denial-of-service (DDoS) attacks, or even tools for physical disruption and espionage. The problem is structural. Many IoT and OT devices ship with default credentials, receive infrequent (or no) firmware updates, lack
Apr 2, 2026 · via securityboulevard.com
Industrial IoT has become a central component of modern industrial systems, driven by the need to improve operational efficiency, resilience and visibility across increasingly complex environments. As industrial assets generate growing volumes of data, organizations are looking beyond basic connectivity to extract meaningful insights that can support real-time decision-making and long-term optimization. At its core, Industrial IoT brings together sensors, connectivity and data platforms to bridge the gap between operational technology and enterprise IT systems. This convergence is reshaping how industrial processes are monitored and controlled, while raising new questions around interoperability, cybersecurity and the practical delivery of business value at scale. Key Takeaways - Industrial IoT connects physical industrial assets to digital systems for real-time monitoring and optimization. - It relies on layered architectures combining edge computing, connectivity and cloud platforms. - Use cases span predictive maintenance, asset tracking, energy management and process automation. - Interoperability, security and scalability remain key technical challenges. - Its business value lies in operational efficiency, reduced downtime and data-driven decision-making. What is Industrial IoT (IIoT)? Industrial IoT refers to the application of connected sensors, devices and software systems to monitor, collect and analyze data from industrial operations in real time, enabling improved efficiency, reliability and decision-making. Unlike consumer IoT, Industrial IoT operates in environments where reliability, safety and latency are critical. It integrates operational technology (OT) systems—such as industrial control systems—with information technology (IT) platforms, bridging historically separate domains. Industrial IoT plays a central role in Industry 4.0 initiatives, where data-driven automation and interconnected systems redefine industrial production and infrastructure management. How Industrial IoT works Industrial IoT systems are typically built on a multi-layered architecture that connects physical assets to digital platforms. At the device layer, sensors and actuators are embedded into machinery, equipment or infrastructure. These devices collect data such as temperature,
Apr 2, 2026 · via iotbusinessnews.com
The Most Dangerous Thing in Your Plant Is What You Can’t See Dale Peterson, founder and program chair of S4, threw down the gauntlet at this year’s S4x26 conference in Miami in February 2026 – demonstrate live industrial security in what was a first for the event. He tasked Booz Allen Hamilton to build a fully operational simulated automotive manufacturing environment with real Siemens and Rockwell Automation PLCs, a full SCADA layer running Ignition, and network segments representing a paint and assembly line. Eight security vendors were invited to solve real problems with live industrial equipment at the POC Pavilion. Cisco was one of them. The exercise underscored a truth that too many organizations still struggle to act on: you cannot secure what you cannot see. And in most OT environments, the gap between what operators assume is on their network and what is actually communicating across it remains dangerously wide. Complexity is the Enemy of OT Security Progress Industrial networks were previously not designed with cybersecurity in mind. They were designed to move product, maintain uptime, and keep people safe. Most OT environments have grown organically over decades, resulting in flat architectures where a paint booth controller can freely communicate with an assembly robot across the plant—or with a compromised workstation that was never supposed to be on that segment. Lateral movement across these unsegmented networks remains a leading concern. Yet many organizations remain stuck. The perceived cost of deploying OT security—specialized hardware, overlay architectures, and the risk of disrupting production—creates inertia. Patchwork approaches introduce their own friction, often requiring dedicated appliances and specialized staff that many do not have. Visibility First, Then Segmentation: A Phased Approach That Works The demonstration Cisco and Booz Allen jointly executed at S4x26 was built around a deliberately pragmatic premise: start with asset
Apr 1, 2026 · via blogs.cisco.com
Edge AI is emerging as a critical enabler for next-generation IoT systems, allowing data processing and decision-making to occur closer to where data is generated. As connected devices proliferate across industries, the limitations of centralized cloud processing—particularly in terms of latency, bandwidth, and privacy—are becoming increasingly evident. By integrating artificial intelligence directly into edge devices or local gateways, Edge AI reshapes how IoT architectures are designed and deployed. It enables faster responses, reduces dependency on network connectivity, and supports new classes of applications that were previously impractical with cloud-only approaches. Key Takeaways - Edge AI brings data processing and AI inference closer to IoT devices, reducing latency and bandwidth usage. - It enables real-time decision-making in environments where cloud connectivity is limited or unreliable. - Key technologies include embedded AI chips, lightweight machine learning models, and edge computing platforms. - Use cases span industrial automation, smart cities, healthcare, logistics, and energy management. - Challenges include hardware constraints, model optimization, security risks, and lifecycle management. What is Edge AI for IoT: Use Cases, Benefits and Deployment Challenges? Edge AI refers to the deployment of artificial intelligence algorithms directly on IoT devices or edge computing infrastructure, enabling data processing and inference to occur locally rather than in centralized cloud environments. Within the IoT ecosystem, Edge AI plays a pivotal role by allowing connected devices—such as sensors, cameras, and industrial machines—to analyze data in real time. This approach reduces reliance on continuous cloud connectivity and supports applications that require immediate insights or actions. Unlike traditional cloud-based AI, where raw data is transmitted to remote servers for processing, Edge AI enables localized intelligence. This shift is particularly relevant for latency-sensitive and bandwidth-constrained use cases. How Edge AI for IoT: Use Cases, Benefits and Deployment Challenges works Edge AI architectures typically combine IoT devices, edge
Apr 1, 2026 · via iotbusinessnews.com
Cyber Threat Alliance Welcomes Motorola Solutions as Newest Member Company brings a new perspective to the Alliance as a leading provider of mission-critical technologies Cyber Threat Alliance (CTA), a nonprofit organization dedicated to improving the cybersecurity of the global digital ecosystem, today announced Motorola Solutions as its newest member and first in the safety and security technology sector. CTA and Motorola Solutions, including the Public Safety Threat Alliance (PSTA) it founded and administrates, will collaborate on cyber threat intelligence sharing to strengthen the security postures of public safety agencies and enterprises globally. Motorola Solutions is a global leader in mission-critical safety and security technologies for public safety, defense and enterprise organizations. Its robust ecosystem includes critical communications, command center, video security and AI technologies that help protect people, property and places. It established the PSTA in 2022, which provides nearly 2,500 public safety agencies globally with actionable intelligence to defend against attacks. “I am pleased to welcome Motorola Solutions to the Cyber Threat Alliance,” said Michael Daniel, President and CEO, Cyber Threat Alliance. “Motorola Solutions brings a new perspective to the Alliance as a leading provider of mission-critical technologies that protect our communities and as the trusted leader for cyber threat intelligence sharing in the public safety sector through the Public Safety Threat Alliance. CTA members look forward to welcoming Motorola Solutions and the enhanced cyber threat collaboration that will ensue.” “All public safety agencies require a mission-critical cybersecurity posture to support the safety and security of their communities,” said Jay Kaine, Director of the PSTA, Motorola Solutions. “We look forward to collaborating with the Cyber Threat Alliance. Together, we will deliver earlier warnings and greater intelligence to the thousands of agencies that depend on this robust knowledge-sharing network to help stay ahead of increasingly sophisticated cyber threats.”
Apr 1, 2026 · via criticalcommunicationsreview.com
- Today - Holidays - Birthdays - Reminders - Cities - Atlanta - Austin - Baltimore - Berwyn - Beverly Hills - Birmingham - Boston - Brooklyn - Buffalo - Charlotte - Chicago - Cincinnati - Cleveland - Columbus - Dallas - Denver - Detroit - Fort Worth - Houston - Indianapolis - Knoxville - Las Vegas - Los Angeles - Louisville - Madison - Memphis - Miami - Milwaukee - Minneapolis - Nashville - New Orleans - New York - Omaha - Orlando - Philadelphia - Phoenix - Pittsburgh - Portland - Raleigh - Richmond - Rutherford - Sacramento - Salt Lake City - San Antonio - San Diego - San Francisco - San Jose - Seattle - Tampa - Tucson - Washington Digi International Launches Rugged 5G Router for Industrial IoT New Digi IX25 device offers active eSIM, edge computing, and AI-driven operations. Apr. 1, 2026 at 1:05am Got story updates? Submit your updates here. › Digi International, a leading provider of IoT connectivity products and services, has announced the launch of the Digi IX25, a next-generation rugged 5G router designed for industrial IoT applications. The device features active eSIM capabilities, edge computing power, and AI-driven operations to support advanced connectivity and edge processing needs. Why it matters The Digi IX25 represents a significant advancement in industrial networking hardware, providing enterprises with a highly capable and secure 5G router to power their IoT deployments. As 5G networks continue to expand, having access to ruggedized, TAA-compliant hardware will be crucial for organizations looking to leverage the speed and low latency of the new wireless standard. The details The Digi IX25 is designed to withstand harsh industrial environments, with a rugged enclosure and support for wide temperature ranges. It offers active eSIM capabilities, allowing for remote SIM provisioning and management,
Apr 1, 2026 · via nationaltoday.com
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