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IOT News
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What Are the Top Hurdles to IoT Adoption in 2024?
- Security threats remain the biggest hurdle to IoT adoption, especially at the "perception layer." This is due to device spoofing, physical tampering, node capturing, and signal jamming. eSIM and its corresponding SGP 3.2 standard hold the potential for enhancing security in IoT ecosystems. eSIM devices enable remote and bulk management of device profiles, thereby enabling swift security updates and patches. Edge IoT devices may help relieve the security burden on IoT networks, by processing data locally. Organizations rely on managed IoT service providers that offer end-to-end support. Technical support remains a persistent challenge for businesses.
- Only 0.4% of organizations across the US and UK are responsible for establishing connectivity of 98% of the devices.
- IoT devices often have limited processing power and memory, which makes it challenging to integrate traditional security features, such as firewalls or encryption protocols, leaving them more vulnerable to attacks.
- The SGP.32 standard, a feature of eSIM IoT, introduces several security enhancements that can fortify the perception layer against potential breaches.
- Edge IoT devices decrease the exposure to external threats, including interception and manipulation during data transmission.
- Managed IoT service providers offer end-to-end support from device deployment to ongoing monitoring and security updates, ensuring operational efficiency and data security.
- Organizations in agritech and manufacturing are particularly keen on processing data at the edge, driven by concerns over privacy, security, and unreliable centralized data processing.
- A lack of adequate technical support continues to impede IoT adoption, with businesses relying on managed IoT service providers for end-to-end support.
- Navigating the complexities of eSIM transitions and securing IoT networks at scale will require navigating through entirely different sets of hurdles.
- Businesses still face considerable hurdles in managing connectivity, ensuring security across multiple layers, and obtaining adequate technical support.
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Medium
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The Grand Unified Theory of Web3.0 and Web3
- Web3.0 originated in 2003; blockchain is a protocol for value transmission while represented as the main architecture of the third-generation web, Web3.0
- Web3.0 aims to achieve decentralization and user data autonomy to address issues such as centralized data monopolies and privacy leaks.
- Web3.0 protocols, such as SOLID proposal, aim to achieve data autonomy and decentralization.
- In Web3.0, protocols like SOLID focus upon separating data from applications which returns data ownership to users.
- Henry proposed “The Grand Unified Theory of Web3.0 and Web3” as Web3 becomes an abbreviation for Web3.0.
- MetaLife.Social integrates SOLID with blockchain cryptocurrency incentives, representing the real Web3.0 protocol stack.
- Web3.0 protocol stack will empower each user to own their share of the internet and tokens in the new era will be supported by data value.
- Running large language models on centralized GPU infrastructure cannot protect personal privacy, only decentralized Web3.0 AI agents can protect users' privacy.
- Only a combination of decentralized (privacy-protecting) AI and centralized (open) AI can be a sustainable path forward for all of humanity.
- The combination of AI + DePIN + DeSoc forms the most ambitious narrative to release and reallocate the data-value wealth of humanity and the entire physical world.
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Pymnts
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Partnerships Become Central to Building a Connected Commerce Future
- Partnerships and collaboration are key in building a connected commerce future.
- Connected devices provide opportunities for quick adoption of digital payments.
- Integration of payments into connected devices is not new, with early examples like open tolling systems.
- Collaboration within industries can create new revenue streams and enhance user experiences.
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Medium
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Understanding the Internet of Things (IoT): A Comprehensive Technical Overview
- The Internet of Things (IoT) is the networking of physical objects with embedded electronics.
- IoT architecture consists of five layers: Perception Layer, Network Layer, Middleware Layer, Application Layer, and Business Layer.
- IoT technology has applications in consumer, industrial, and urban sectors.
- IoT systems offer benefits such as automation, cost savings, improved decision-making, enhanced safety, and convenience.
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Securityaffairs
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PTZOptics cameras zero-days actively exploited in the wild
- Hackers are actively exploiting two zero-day vulnerabilities, CVE-2024-8956 and CVE-2024-8957, in PTZOptics cameras.
- The vulnerabilities allow unauthorized access to sensitive information and OS command injection, potentially leading to full system control.
- These exploits can jeopardize video feeds, compromise sensitive sessions, and enable botnet participation for DDoS attacks.
- Affected organizations are advised to apply firmware updates immediately and ensure system security.
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Embedded
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Silicon IC Intellectual Property Design, AIoT, Battery Cell Monitoring: Embedded Week Insights
- Siemens has acquired Altair Engineering Inc., a leading software supplier in the industrial simulation and analysis sector.
- Quantum sensors can enhance the precision and dependability of position, navigation, and timing (PNT) devices, according to a report by QED-C.
- The current landscape of chip design ownership and sharing balances safeguarding intellectual property and encouraging collaboration.
- AI has transformed connected devices, revolutionizing automation and efficiency in homes, workplaces, and cities.
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Alvinashcraft
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Dew Drop – October 31, 2024 (#4291)
- Blazor in .NET 9 with Dan Roth is discussed on .NET Rocks! by Carl Franklin and Richard Campbell.
- Building AI Assistants with Microsoft Copilot Studio is covered by Siva Saripilli.
- Create a Flutter Semi-Doughnut Chart to Visualize Transport Emissions per Kilometer Traveled tutorial is written by Aswini Suresh Reddy.
- Unreal Engine Toolbar in Visual Studio article is published by David Li.
- State of CSS 2024 Results post by Geoff Graham presents the results.
- SQL Server for Visual Studio Code (Visual Studio Code Marketplace) October release includes a connection dialog, table designer, new query results pane, query plan viewing, and object explorer filtering.
- Integrate data from external sources into Microsoft Entra tokens using the Authentication Events library post by Abdul Hakim.
- Azure Bicep: Parameter Files for Streamlined Infrastructure as Code (IaC) tutorial is written by Chris Pietschmann.
- .NET Aspire 9.0 RC1: Simplified Setup, Azure Functions Support Added, and Other Improvements post is published by Almir Vuk.
- GitHub Copilot for Azure: 6 Must-Try Features post is shared by Amy Boyd.
- Introducing SimpleQA post is published by OpenAI Team.
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Bigdataanalyticsnews
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Intelligent Operations: Why do Technology Leaders Need this Pivot?
- A software-oriented organizational strategy must be managed and operated. Technology can no longer be detached from an organization’s value chain.
- The solution is to have an AI-fueled solution portfolio designed to transform IT and Operations so that they move at the speed of the business.
- Intelligent Operations Solutions must be adopted by businesses to drive automation, analytics, and more.
- Synergize, strategize, and streamline are the three-tiered strategies to optimize business operations with an AI-led approach.
- Key points on how intelligent operations make an enterprise smarter and faster include intelligent full-stack observability, AI-driven service management, infrastructure intelligent automation and orchestration, autonomous endpoint management, and policy and compliance management.
- AI plays a pivotal role in analyzing data and driving organizational transformation to run businesses successfully.
- Customer experience enhancement, error reduction, automation impact, complex problem-solving, operational efficiency, and better decisions are some of the many benefits of AI-driven intelligent operations.
- Successful adoption of intelligent operations in businesses requires setting initial objectives, mapping current processes, setting the architectural vision for these efforts, and driving operational transformation.
- A well-thought AI strategy and implementation of the right tools can help organizations develop a cutting-edge IT ecosystem.
- Intelligent operations are key to transforming IT operations, generating business and shareholder value, and improving the organization’s overall performance.
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AIoT – How Artificial Intelligence is Transforming Connected Devices
- The integration of AI into IoT devices has revolutionized various sectors, including predictive monitoring, industrial automation, autonomous driving, and smart home devices.
- AI algorithms analyze data from IoT sensors, identify inefficiencies or anomalies, and automatically adapt the production process, reducing waste and operating costs.
- The ability to predict and prevent problems helps reduce downtime, enhances product quality, and represents a competitive advantage, especially in sectors where operational continuity is critical.
- Smart home devices have seen exponential growth in recent years, with connected devices that use AI to learn from users' habits and adapt to their needs proactively, improving security and energy efficiency.
- AI in IoT devices requires access to large amounts of personal and sensitive data, raising concerns about data security and privacy. Robust security measures must be implemented to protect data during both transmission and storage.
- SenseCAP A1101 is an innovative series of IoT devices with integrated AI, specially designed for application scenarios in smart industrial and agricultural environments.
- Broadcom offers several categories of products designed to support AI of Things applications, such as optical and imaging sensor solutions that are essential for real-world use cases that require visual processing.
- Efficient network management is critical for applications that need to process large volumes of sensor data to facilitate the rapid exchange of information between IoT devices and AI, and Broadcom provides chips designed for cutting-edge networks that support infrastructures.
- As AI continues to evolve, we can expect to see more capabilities in connected devices that improve operational efficiency on a massive scale.
- Despite the challenges of data security and privacy, the potential of AI in IoT is enormous, and the opportunities for innovation and growth are virtually limitless.
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Dev
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Creating an IoT Device Frontend: A High-Level Overview
- The Smart Dustbin was designed to create an intelligent waste management system that monitors the fill level of a dustbin, measures various environmental parameters and alerts stakeholders when the dustbin needs to be emptied.
- The project was divided into three main components: the IoT device, the server, and the frontend dashboard.
- The IoT device used NodeMCU microcontroller, which provides built-in Wi-Fi support. The entire code for the device was written in C++. Data was sent to an MQTT server over a wireless connection.
- The server played a pivotal role in the project as it managed real-time data, stored it in the database, and communicated with the frontend.
- The frontend involved extracting meaningful data from server responses and presenting it in a user-friendly manner. The server sent a string of data containing various information.
- The key functionalities included trash level monitoring, mapping, and gas monitoring. The server sent a string of data through MQTT and Socket.IO for this purpose.
- Challenges included parsing string data, displaying real-time updates without affecting the UI's responsiveness, and visualizing sensor data. Each component of the project brought unique challenges but by leveraging the strengths of each technology, we were able to create a seamless system that effectively managed and displayed real-time IoT data.
- The final product was a fully functioning Smart Dustbin system that provided live updates on the trash fill level, monitored various environmental parameters, and used map integration to show its exact location.
- The project provided valuable hands-on experience with technologies like MQTT, Node.js, Socket.IO, Firebase, and React. It was an enriching project and an idea of how you can approach similar IoT projects.
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Medium
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Towards a Sustainable Future: Harnessing AI, Blockchain, and IoT for Environmental Stewardship
- Artificial intelligence (AI), blockchain, and the Internet of Things (IoT) are key tools in promoting a sustainable future.
- AI can evaluate large databases, create insights, and contribute to smart cities, agriculture, energy optimization, and predictive maintenance.
- Blockchain technology enhances supply chain management, promotes responsibility, and enables peer-to-peer energy trading.
- The Internet of Things (IoT) improves efficiency, resource management, and water conservation in areas like smart transportation systems and agriculture.
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Dzone
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Exploring Foundations of Large Language Models (LLMs): Tokenization and Embeddings
- Generative AI application stores data from multiple sources, and queries the data to generate human language responses.
- Tokenization is the process of breaking down human text into smaller units assigned with token IDs that can be processed by models.
- There are various types of tokenization like sentence-level, word-level, subword, character-level, and hybrid tokenizer to optimize efficiency and flexibility.
- Embedding is the process of converting tokenized text to numerical format, enabling the model to process it.
- There are three known types of embeddings: traditional word embeddings, contextual embeddings, and positional embeddings.
- To generate human-like outputs, user query vectors are compared with corpus vectors through cosine similarity or Euclidean distance.
- Tokenization and embeddings are two critical processes that enable LLMs to process and generate human language.
- As GenAI evolves, improving tokenization methods and embeddings will be important to build more efficient and powerful language models.
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Dev
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Unlocking the Future of Building Management with AWS IoT
- Implement IoT solutions using AWS IoT without AWS Greengrass with three effective strategies.
- Key challenges addressed include limited device compatibility, underutilization, vendor agnosticism, and integration.
- To optimize resources and reduce costs, expand IoT device usage, enhance vendor integration, and ensure reliable data collection.
- We can explore innovative paths to smarter building management and a more efficient future.
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Siliconangle
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Qualcomm and Google to collaborate on more intelligent cars with integrated generative AI
- Qualcomm and Google are collaborating to enhance the intelligence of cars with integrated generative AI.
- The partnership will integrate Qualcomm's Snapdragon Digital Chassis and Google's Android Automotive OS software.
- Developers will be able to create generative AI-enabled digital cockpits with advanced voice assistants and immersive maps.
- The collaboration aims to provide safe and digitally advanced experiences in cars.
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Embedded
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MIKROE Launches the New LR 11 Click Board, Enabling Ultra-Low Power 915MHz LoraWAN Data Communications for IoT
- MIKROE has launched LR 11 Click, a new add-on board that enables ultra-low power 915MHz LoraWAN data communications for IoT.
- The LR 11 Click incorporates the Ezurio's 453-00139R LoraWAN module, which integrates the Silicon Labs EFR32 SoC and the Semtech SX1262 radio.
- It is compatible with LoRaWAN classes A, B, and C, has a communication range of up to 15km, and supports peripherals through an additional mikroBUS connection.
- The LR 11 Click is entirely compatible with the mikroBUS socket and comes with mikroSDK libraries and ClickID capability for easy recognition.
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