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Artificial intelligence voice recording technology has developed rapidly over the past few years, revolutionizing the way we record and engage with sound. An AI voice recorder uses smart technology to record and improve sound quality. Unlike traditional recorders, AI-powered devices remove background noise, enhance voice clarity, and convert speech into text. This technology has transformed industries like media and entertainment, which generated the highest revenue in 2023. Building your own AI voice recorder offers numerous benefits: - Cost-effectiveness compared to hiring voice-over services - Time savings through automated transcription and processing - Customization to fit your specific needs - Control over features and functionalityThe AI voice tools market, valued at $3.56 billion in 2023, is growing rapidly and is projected to reach $10.8 billion by 2030. This growth is driven by the ability to provide users with personalized experiences and enhanced productivity.Understanding the BasicsBefore developing an AI voice recorder, it’s essential to understand sound signal processing and AI technology. Current AI voice technology relies on deep learning and neural network models to improve voice recognition accuracy.Key Concepts:Sound Signal Processing: Converting analog audio signals into digital data that computers can processAI and Machine Learning: Using techniques like deep learning to analyze and interpret audio data, enabling features such as speech-to-text conversion and audio summarizationHardware ComponentsSelecting the right hardware components is critical for an AI voice recorder. Each component works together to capture high-quality sound and process it effectively using AI algorithms.1. MicrophoneA good microphone is crucial for capturing clear audio. Look for microphones with a cardioid pattern to focus on your voice while reducing background noise.Options: - USB Microphones: Simple to use and affordable for beginners (Blue Yeti, Audio-Technica AT2020) - XLR Microphones: Require an audio interface but provide better sound qualityTips: - Position the microphone 4-6 inches from your mouth - Use a pop filter to block harsh sounds2. ProcessorA high-performance processor is necessary to handle microphone input and efficiently execute AI algorithms. Multi-core processors are ideal for real-time processing.Requirements: - At least 8GB of RAM (16GB recommended for faster processing) - Multi-core processor - GPU like NVIDIA RTX for enhanced performance (optional)Options: - Raspberry Pi for simple projects - ESP32 for portable applications - More powerful processors like Intel Xeon W for demanding tasks3. Sound CardA sound card converts analog audio signals to digital data that can be processed by AI algorithms.Popular options: - USB Sound Cards like Focusrite Scarlett series4. Storage DeviceAdequate storage is necessary for both audio recordings and generated text content.Options: - MicroSD cards for devices like Raspberry Pi - SSDs for more powerful setups - Cloud storage for scalability5. Power Supply (Battery)For portable recorders, a reliable battery ensures operation for extended periods without interruption.Preferred choice: - Rechargeable lithium-ion batteries - Energy-efficient components to maximize battery life6. Audio Output Components (Optional)For voice assistants or real-time feedback, speakers or headphones may be necessary.Examples: - 3W, 4Ω Speakers for delivering audio responsesComponentDescriptionExamplesMicrophoneCaptures clear audio. Multi-directional microphones are preferred.Blue Yeti, INMP MicrophoneProcessorHandles AI algorithms and audio processing. Multi-core processors are ideal.Raspberry Pi, ESP32, Intel Xeon WSound CardConverts analog audio to digital data.Focusrite Scarlett seriesStorage DeviceStores audio recordings and AI models.MicroSD Cards, SSDsPower SupplyEnsures continuous operation. Rechargeable batteries are common.Lithium-ion batteriesAudio OutputOptional for real-time feedback.3W, 4Ω SpeakersSoftware and Programming Environment SetupSetting up the right software and programming environment is vital for developing an AI voice recorder.Essential SoftwareAudio Recording ProgramsYou need software to record sound: - Audacity: Free and works on most computers with tools for editing and noise removal - GarageBand: Great for Mac users and easy to useAI Tools for Voice FeaturesAI frameworks add smart capabilities to your recorder: - TensorFlow: Easier for beginners with extensive documentation - PyTorch: Better for experimentation and researchDevelopment ToolsPython: Primary programming language with libraries like speech_recognition or pyaudioReplit: Platform for backend development and deploymentCursor AI: Coding environment for integrating AI modelsSetup StepsOperating System: Install a compatible OS (like Raspbian for Raspberry Pi)Development Tools: Install Python and necessary librariesSpeech Recognition APIs: Integrate APIs like Google Speech API or CMU SphinxExample Code (Python)import speech_recognition as sr# Create a speech recognition objectr = sr.Recognizer()# Use the microphone as the audio sourcewith sr.Microphone() as source:    print("Please say something:")    audio = r.listen(source)try:    # Convert speech to text    print("You said: " + r.recognize_google(audio))except sr.UnknownValueError:    print("Google Speech Recognition could not understand audio")except sr.RequestError as e:    print("Could not request results from Google Speech Recognition service; {0}".format(e))Cloud AI Services and APIsCloud services extend the capabilities of your AI voice recorder, especially if your hardware is limited.Cloud AI PlatformsGoogle Cloud: Offers speech-to-text, natural language processing, and other AI servicesAWS: Provides comprehensive AI tools through Amazon Web ServicesAPIs for Speech and TextOpenAI Whisper: Provides accurate transcription across multiple languagesGoogle Speech API: Offers robust speech-to-text capabilitiesCMU Sphinx: An open-source speech recognition systemAI Voice Cloning PlatformsElevenLabs: User-friendly voice cloning with free trialsResemble AI: Upload voice samples to train AI to replicate themTopMediai Voice Cloning: Create personalized AI voices using advanced machine learningRecording High-Quality AudioBest PracticesSelect a quality microphone appropriate for your needsMaintain proper microphone positioning (4-6 inches from mouth)Use headphones to monitor audio quality in real-timeAdd a pop filter to minimize plosive soundsRecord in a quiet environment to minimize background noiseCapture some ambient sound for easier editingSave recordings in WAV format for the highest qualityFile FormatsWAV: Uncompressed, highest quality, ideal for editing and AI processing (larger file size)MP3: Compressed format, smaller file size, good for sharing or storageFLAC: Lossless compression, good balance between quality and sizeIntegrating AI ModelsSteps to Integrate AI Models1. Choose an AI ModelSelect a suitable model based on your requirements: - Speech recognition - Emotion detection - Audio summarization2. Train or Use Pre-trained ModelsPre-trained models: Save time by using models that are already trainedCustom training: Train models with your specific data for better resultsBenefits of pre-trained models: - Save development time - Require less computational power - Work well even with limited data - Can be fine-tuned for specific needs3. Training Steps for Custom ModelsData Collection: Gather diverse audio samplesData Preprocessing: Clean and normalize the dataModel Training: Train using deep learning techniques (RNNs, CNNs)Testing: Evaluate with various speech patterns and accents4. IntegrationUse APIs or libraries to integrate the model into your voice recorder.5. Testing and OptimizationPerformance Evaluation: Assess recognition accuracy and response timeFeedback Iteration: Improve based on user feedbackError Reporting: Use logs to identify and fix issuesAdvanced Features1. Automatic TranscriptionConvert audio recordings to text automatically, saving time and enhancing productivity.Implementation options: - Use speech recognition APIs like Google Speech API - Implement custom models with TensorFlow or PyTorch - Integrate OpenAI Whisper API for high accuracy2. Noise Cancellation and Audio EnhancementAI tools can remove unwanted sounds and enhance voice quality: - Spectral subtraction: Removes consistent background noise - AI-based denoising: Learns to separate voice from noise - Compression: Evens out volume differences3. Voice CloningVoice cloning uses AI to replicate someone’s voice by analyzing pitch, tone, and rhythm:How it works: 1. The AI studies audio samples to learn voice characteristics 2. Deep learning processes large datasets to create realistic results 3. The trained model can generate speech that sounds like the original speakerTools for creating cloned voices: - ElevenLabs: User-friendly with free trial options - Resemble AI: Upload voice samples to train the AI - Tacotron 2: More control for advanced users4. Text-to-Speech (TTS)Convert written text into spoken words with natural-sounding voices: - Great for audiobooks, virtual assistants, or accessibility features - Advanced TTS allows customization of tone and speaking rate5. Multi-Language SupportAdding support for multiple languages makes your recorder useful worldwide: - Train with multilingual datasets - Use pre-trained models like OpenAI Whisper that already support many languages - Essential for global businesses or projects6. AI-Generated AvatarsCombine voices with visual animations to create lifelike characters: - Copy facial expressions and lip movements - Useful for virtual meetings or media projects - Tools like Synthesia pair your AI voice with avatarsUser Interface and Interaction DesignA well-designed interface improves user experience and makes your AI voice recorder more accessible.Design Principles: - User-Friendly Interface: Use clear and simple controls - Sound Feedback: Provide audio cues for user actions - Visual Indicators: Display recording status and errorsTools for Design: - Tkinter or PyQt for creating GUIs in PythonManaging and Storing RecordingsOrganizing FilesCreate a logical folder structure based on: - Projects - Dates - Content typesUse clear naming conventions like “Podcast_Episode1_2023.wav” for easy retrieval.Backup StrategiesImplement multiple backup methods: - Cloud storage (Amazon S3, Google Cloud Storage) - External drives for local backup - Regular update schedule to include new recordingsOptimizing PerformanceReducing LatencyLow latency is crucial for real-time applications: - Keep latency under 500ms for smooth communication - Aim for 20-50ms for the best experience - Use edge computing to process data closer to users - Implement lightweight models for faster processingBalancing Quality and SpeedBoth audio quality and processing speed are important: - Use noise filters and high-quality codecs - Implement automatic gain control (AGC) for voice enhancement - Preprocess data with noise samples for better real-world performancePractical Applications1. Business and MeetingsAutomatic transcription of discussionsMeeting note-taking without manual effortSeamless sharing of transcriptions with team members2. Education and LearningCapturing lectures and discussionsAllowing students to focus on understanding rather than note-takingCreating a more inclusive learning environment3. Personal ProductivityManaging tasks and ideas efficientlyBrainstorming and journaling on the goIntegration with productivity apps4. Interviews and JournalismCapturing accurate quotes without manual note-takingFocusing on the conversation rather than documentationPost-interview processing and organization5. Accessibility and HealthcareReal-time transcriptions for those with hearing impairmentsEnhanced communication in healthcare settingsDocumentation of patient interactionsFuture Outlook and ChallengesEmerging TrendsAdaptive Learning: AI models that improve by learning from user speech patternsVoice Emotion Recognition: Detecting emotional states from voice characteristicsAdvanced Voice Cloning: Creating more natural and personalized voice replicasChallengesPrivacy Concerns: Ensuring user data security and consentBias in AI Models: Addressing biases in speech recognition systemsEthical Use: Preventing misuse of voice cloning technologyCommon QuestionsQ1: What is the best microphone for an AI voice recorder?A1: The best microphone depends on your environment and quality requirements. USB microphones like Blue Yeti or Audio-Technica AT2020 are popular for their clarity and ease of use. For professional applications, XLR microphones with an audio interface provide superior quality.Q2: How much does it cost to build an AI voice recorder?A2: Costs vary based on component selection. A basic setup with a USB microphone and free software like Audacity can cost under $100. More advanced setups with professional microphones, interfaces, and cloud services may exceed $500.Q3: Do I need coding skills to build an AI voice recorder?A3: While coding knowledge helps, it’s not always required. Many tools and APIs provide user-friendly interfaces. Basic Python skills are beneficial for customization and integration.Q4: Can I use my AI voice recorder for live streaming?A4: Yes, with proper optimization for low latency. Use edge computing and lightweight models to minimize delays, and test thoroughly with streaming applications.Q5: How do I improve the accuracy of my AI voice recorder?A5: Improve accuracy by training with diverse datasets, optimizing hardware settings, using high-quality microphones, and minimizing background noise.Q6: Is voice cloning safe to use?A6: Voice cloning should be used ethically. Always obtain permission before cloning someone’s voice, and be aware of potential privacy and security implications.Kynix: Your Trusted Partner for AI Voice Recorder ComponentsPurchasing dependable, high-quality electronic components is crucial for achieving the best possible performance while developing an AI voice recorder.  Leading international distributor of electronic components, Kynix, provides a wide selection of parts designed especially for AI and audio applications.ConclusionBuilding an AI voice recorder requires understanding hardware and software components, integrating appropriate AI models, and focusing on user experience. With the right components and approach, you can create a powerful tool that enhances productivity and accessibility.As AI technology continues to evolve, voice recorder capabilities will expand, making these devices increasingly valuable in our personal and professional lives. Whether you’re a beginner experimenting with basic components or an advanced developer pushing the boundaries of what’s possible, creating your own AI voice recorder is an exciting project with practical applications.ReferencesReddit: RambleFix - A voice recorder that uses AI to convert messy thoughts into clear textco: AI Meeting Notes GuideScreenApp: Audio Summarizercom: Open Source AI Voice Projectsio: Audio Data Collectionai: Top AI Voice RecordersHardware Development of Voice Recorder with AI Minutes Creation FunctionAI Voice Hardware Requirements Compatibility Guidefm: Recording High-Quality AudioGrand View Research: AI Voice Generators Market

Overview: This article explores the opportunities and challenges of integrating clean technologies and information and communication technologies for efficient and sustainable energy management in smart grids.  Decarbonization has accelerated the fundamental shift in society toward clean technologies. Electrical energy will be a significant factor in the decarbonization process. Electrical energy is one of the most common forms of energy carriers and is seeing growing usage. Increasing electricity demand forces the expansion of the generation and transmission systems, requiring a significant amount of investment.  Power loss and reactive power flow in the transmission systems make the conventional, centralized structure of power systems less efficient. Distributed generations (DGs) have been incorporated into low- and medium-voltage distribution networks in order to increase system availability, efficiency, and cost-effectiveness. Furthermore, renewable-based distributed generation aids in the decarbonization of the electric energy sector.Evolution of Smart GridDistribution systems that have been powered up can function as a microgrid in the absence of the utility grid. A microgrid is an island-based distribution system that uses local distributed generation and energy storage to provide critical loads in island mode. Distribution systems with microgrid capabilities will have some benefits, such as increased productivity, dependability, accessibility, and power quality.  However, information and communication technologies (ICTs) are necessary for the optimal and reliable operation of various distributed generation and energy storage systems in microgrids. To operate modern energy distribution systems as efficiently and dependably as possible, the smart grid concept has been introduced. To operate and plan grid systems with irregular output and variable power sources, ICTs must be available at both the generation and transmission levels. These systems enable power systems to meet customer demands by intelligently monitoring, making decisions, and controlling contemporary power systems. In addition to incorporating DGs into distribution networks, large-scale renewable power plants like photovoltaic (PV) and wind energy systems have been widely installed in power systems, and the power grids are currently moving toward more fully renewable energy systems. Figure 1. Concept of a Distributed Power Generation System Source IEEE Access Along with efficiency, flexibility, and operability benefits, smart grid technologies also present new difficulties for the design and management of modern power systems. Restructuring the power grids to incorporate renewable energy sources, microgrid technologies, ICTs, and power electronics can result in these difficulties. Smart Grid’s Future DirectionsThe idea of smart grids has changed with the development of technology. In recent years, the smart grid's research and development have increased. As a result, the implementation of smart grids has changed from virtual to real-time. However, there are several situations in which action needs to be taken to turn it into a complete real-time network service.Big Data ManagementThe input of real-time data is a key factor in a smart grid. It serves as the backbone of the network's functioning. Power transmission, generation, transformation, and utilization data are being collected for reliable and efficient working. All decisions are made based on the information gathered. The collection and management of such a vast amount of real-time data is a significant problem.  To predict the demand for energy at various locations, the algorithms must use all the data gathered from the sensors and associated devices. To produce the best results, the algorithms must be optimized. One of the main study subjects in smart grid technology is IT infrastructure, data gathering, governance, data processing, and, most critically, data security.Investing in Smart Grid InfrastructureTo reduce carbon emissions, a number of countries have started implementing smart grid infrastructure. Many of them are engaged in projects designed to evaluate the feasibility of the network. The construction of the smart grid infrastructure has already started in nations including Australia, South Korea, and Japan. The initial investment, though, is the main concern. The ongoing maintenance of the entire network further raises the overall cost.  Therefore, before making an investment of this size in the infrastructure, a thorough financial report should be made. The price of smart grids in a few emerging nations is shown in Table 1. This will estimate the starting sum that a developing nation must invest in order to create smart grid infrastructure. Additionally, it will provide a general concept of the maintenance costs as well as any other extra expenses necessary to guarantee the network's efficient operation.Business Model RestructuringThe business model has undergone considerable adjustment as a result of the new smart grid's emergence. New technologies have altered consumer perceptions and created a network of distributed power sources. Consequently, business practices are evolving. It is necessary to implement new policies to benefit consumer communications. To integrate the load and the generated power, the utility business model should be put into practice at the distribution level.Modernization of the Energy Production SystemCustomer needs have evolved due to the smart grid's evolution. As a result, there are fluctuations in energy demand. To accommodate the demand response, the system's capacity should be raised. Additionally, the energy-producing systems must change their production policies to integrate into the smart grid network. In the smart grid network, cloud-based data management strategies are applied. The existing system needs to be upgraded and changed in order to establish IoE activities.  Cyber-physical power systems are the smart operation of future power systems, which include distributed generation, microgrids, and demand side management while utilizing information and communication technologies over the physical system. The ICTs are vulnerable to cyberattacks, data loss, and hardware failure. ICT malfunctions will reduce system performance and must be taken into account when planning a power system. Additionally, when operating power systems, cybersecurity must be taken into consideration because malicious intrusions from cyberattacks could result in a loss of power or energy. The network should incorporate security measures against cyberattacks.Summarizing the Key PointsThe paper highlights the importance of information and communication technologies in the optimal and reliable operation of distributed generation and energy storage systems in microgrids.The integration of information and communication technologies with power systems can lead to the development of cyber-physical power systems or smart grids.Smart grids enable power systems to meet customer demands by intelligently monitoring, making decisions, and controlling contemporary power systems.However, the adoption of clean technologies and information and communication technologies presents new challenges for the design and management of modern power systems.Smart grid technologies also present new difficulties for design and management but offer significant benefits such as flexibility, efficiency, operability, reliability, accessibility, and power quality. Reference(s)1.Peyghami, S., Palensky, P., & Blaabjerg, F. (2020). An Overview on the Reliability of Modern Power Electronic Based Power Systems. IEEE Open Journal of Power Electronics, 1, 34–50. https://doi.org/10.1109/ojpel.2020.29739262.Pal, R., Chavhan, S., Gupta, D., Khanna, A., Padmanaban, S., Khan, B., & Rodrigues, J. J. P. C. (2021, August 28). A comprehensive review on IoT‐based infrastructure for smart grid applications. IET Renewable Power Generation, 15(16), 3761–3776. https://doi.org/10.1049/rpg2.122723.Rafique, Z., Khalid, H. M., & Muyeen, S. M. (2020). Communication Systems in Distributed Generation: A Bibliographical Review and Frameworks. IEEE Access, 8, 207226–207239. https://doi.org/10.1109/access.2020.3037196   

A new, environmentally-friendly electronic alloy consisting of 50 aluminum atoms bound to 50 atoms of antimony may be promising for building next-generation "phase-change" memory devices, which may be the data-storage technology of the future, according to a new paper published in the journal Applied Physics Letters, which is produced by AIP Publishing.Phase-change memory is being actively pursued as an alternative to the ubiquitous flash memory for data storage applications, because flash memory is limited in its storage density and phase-change memory can operate much faster.Phase-change memory relies on materials that change from a disordered, amorphous structure to a crystalline structure when an electrical pulse is applied. The material has high electrical resistance in its amorphous state and low resistance in its crystalline state—corresponding to the 1 and 0 states of binary data.Flash memory has problems when devices get smaller than 20 nanometers. But a phase-change memory device can be less than 10 nanometers—allowing more memory to be squeezed into tinier spaces. "That's the most important feature of this kind of memory," said Xilin Zhou of the Shanghai Institute of Microsystem and Information Technology at the Chinese Academy of Sciences. Data can also be written into phase-change memories very quickly and the devices would be relatively inexpensive, he added.So far, the most popular material for phase-change memory devices contains germanium, antimony, and tellurium. But compounds with three elements are more difficult to work with, Zhou said."It's difficult to control the phase-change memory manufacturing process of ternary alloys such as the traditionally used germanium-antimony-tellurium material. Etching and polishing of the material with chalcogens can change the material's composition, due to the motion of the tellurium atoms," explained Zhou.Zhou and his colleagues turned to a material with just two elements: aluminum and antimony. They studied the material's phase-changing properties, finding that it's more thermally stable than the Ge-Sb-Te compound. The researchers discovered that Al50Sb50, in particular, has three distinct levels of resistance—and thus the ability to store three bits of data in a single memory cell, instead of just two. This suggests that this material can be used for multilevel data storage."A two-step resistance drop during the crystallization of the material can be used for multilevel data storage (MLS) and, interestingly, three distinct resistance levels are achieved in the phase-change memory cells," Zhou says. "So the aluminum-antimony material looks promising for use in high-density nonvolatile memory applications because of its good thermal stability and MLS capacity."  

SummaryResearchers at Caltech have developed a prototype miniature medical device that could ultimately be used in “smart pills” to diagnose and treat diseases. This is critical for the function of biosensors and smart pills. A key to the new technology—and what makes it unique among other microscale medical devices—is that its location can be precisely identified within the body, something that proved challenging before. The picture is about an ATOMS microchip localized within the gastrointestinal tract. bodyCalled ATOMS, which is short for addressable transmitters operated as magnetic spins, the new silicon-chip devices borrow from the principles of magnetic resonance imaging (MRI), in which the location of atoms in a patient's body is determined using magnetic fields. The microdevices would also be located in the body using magnetic fields—but rather than relying on the body's atoms, the chips contain a set of integrated sensors, resonators, and wireless transmission technology that would allow them to mimic the magnetic resonance properties of atoms. The ATOMS device seen next to a penny. The device has a surface area of 1.4 square millimeters, 250 times smaller than a penny. A key principle of MRI is that a magnetic field gradient causes atoms at two different locations to resonate at two different frequencies, making it easy to tell where they are. The researchers wanted to embody this elegant principle in a compact integrated circuit. ATOMS devices also resonate at different frequencies depending on where they are in a magnetic field. The scientists wanted to make this chip very small with low power consumption, and that comes with a lot of engineering challenges. They had to carefully balance the size of the device with how much power it consumes and how well its location can be pinpointed.The devices are still preliminary but could one day serve as miniature robotic wardens of our bodies, monitoring a patient's gastrointestinal tract, blood, or brain. They could measure factors that indicate the health of a patient—such as pH, temperature, pressure, sugar concentrations—and relay that information to doctors. Or, the devices could even be instructed to release drugs. Microscale and Biosensors You could have dozens of microscale devices and biosensors -traveling around the body taking measurements or intervening in disease. These devices can all be identical, but the ATOMS devices would allow you to know where they all are and talk to all of them at once. The researchers compare it to the 1966 sci-fi movie Fantastic Voyage, in which a submarine and its crew are shrunk to microscopic size and injected into the bloodstream of a patient to heal him from the inside—but, instead of sending a single submarine, you could send a flotilla. The researchers say the devices are still preliminary but could one day serve as miniature robotic wardens of our bodies, monitoring a patient's gastrointestinal tract, blood, or brain. The devices could measure factors that indicate the health of a patient—such as pH, temperature, pressure, sugar concentrations—and relay that information to doctors. Or, the devices could even be instructed to release drugs. This chip is totally unique: there are no other chips that operate on these principles. Integrating all of the components together in a very small device while keeping the power low was a big task. The final prototype chip, which was tested and proven to work in mice, has a surface area of 1.4 square millimeters, 250 times smaller than a penny. It contains a magnetic field sensor, integrated antennas, a wireless powering device, and a circuit that adjusts its radio frequency signal based on the magnetic field strength to wirelessly relay the chip’s location. In conventional MRI, all of these features are intrinsically found in atoms. Ther researchers still had to create an architecture that functionally mimics them for our chip. Article from CaltechArticle edit by kynix

At a ceremony today at ESO's Headquarters four contracts were signed for major components of the Extremely Large Telescope (ELT) that ESO is building. These were for: the casting of the telescope's giant secondary and tertiary mirrors, awarded to SCHOTT; the supply of mirror cells to support these two mirrors, awarded to the SENER Group; and the supply of the edge sensors that form a vital part of the ELT's huge segmented primary mirror control system, awarded to the FAMES consortium.  The construction of the 39-metre ELT, the largest optical/near-infrared telescope in the world, is moving forward. The giant telescope employs a complex five-mirror optical system that has never been used before and requires optical and mechanical elements that stretch modern technology to its limits.Contracts for the manufacture of several of these challenging telescope components have just been signed by ESO's Director General, Tim de Zeeuw, and representatives of three industrial contractors in the ESO Member States.Introducing the ceremony, Tim de Zeeuw said: "It gives me great pleasure to sign these four contracts today, each for advanced components at the heart of the ELT's revolutionary optical system. They underline how the construction of this giant telescope is moving ahead at full speed—on target for first light in 2024. We at ESO look forward to working with SCHOTT, SENER and FAMES—three leading industrial partners from our Member States."The first two contracts were signed with SCHOTT by Christoph Fark, Executive Vice President. They cover the casting of the ELT's largest single mirrors—the 4.2-metre secondary and 3.8-metre tertiary mirror—from SCHOTT's low-expansion ceramic material Zerodur.Hanging upside-down at the top of the telescope structure, high above the 39-metre primary mirror, the secondary mirror will be largest ever employed on a telescope and the largest convex mirror ever produced. The concave tertiary mirror is also an unusual feature of the telescope. The ELT secondary and tertiary mirrors will rival in size the primary mirrors of many modern-day research telescopes and weigh 3.5 and 3.2 tonnes respectively. The secondary mirror is to be delivered by the end of 2018 and the tertiary by July 2019.The third contract was signed with the SENER Group by Diego Rodríguez, Space Department Director. It covers the provision of the sophisticated support cells for the ELT secondary and tertiary mirrors and the associated complex active optics systems that will ensure these massive, but flexible, mirrors retain their correct shapes and are correctly positioned within the telescope. Great precision is needed if the telescope is to deliver optimum image quality.The fourth contract was signed by Didier Rozière, Managing Director (FAMES, Fogale), and Martin Sellen, Managing Director (FAMES, Micro-Epsilon), on behalf of the FAMES consortium, which is composed of Fogale and Micro-Epsilon. The contract covers the fabrication of a total of 4608 edge sensors for the 798 hexagonal segments of the ELT's primary mirror [6].These sensors are the most accurate ever used in a telescope and can measure relative positions to an accuracy of a few nanometres. They form a fundamental part of the very complex system that will continuously sense the locations of the ELT primary mirror segments relative to their neighbours and allow the segments to work together to form a perfect imaging system. It is a huge challenge not only to make sensors with the required precision, but also to produce them quickly enough for thousands to be delivered to the necessarily short timescales.The signing ceremony was also attended by other senior representatives of the companies involved and ESO. It was an excellent opportunity for representatives of the contractors producing many of the giant telescope's optical and mechanical components to get to know each other informally as they begin to help create the world's biggest eye on the sky.Reference:GP1S036PKGS-00GXP1-RRB-3R0232-50

Emergency lights assist the vehicles allocated for emergency response services to do better. Emergency lighting units are essential not just as a supplementary light supply, but also as a reliable guide to the normal public. However, LED lights are the most productive emergency lights that can assist emergency vehicles accomplish their responsibilities without inhibitions. Employing diverse colored lights for emergency vehicles boost their competence as guiding lights making them noticeable. Emergency LED lights come in several diverse colors to help the emergency vehicles direct the traffic and employ them as supplementary lighting systems. They're accessible in colors like blue, red, gree, yellow and amber, which can be employed individually or merged into one lightbar. Blue LED lights are most standard lights which can be noticed on police cars, and emergency ambulances.Blue LED lights are also the most productive when merged with other colored lights. Police vehicles employ these in combination with the red light emitting diodes to aware the general public about the emergency circumstance, or execure their patrolling responsibilities without any issues. Different colored LEDs can be assembled to blink in several diverse outlines that make them noticeable from nearly a mile. Though single colored light emitting diodes are noticeable from a distance, blinking manifold colored lightings make superior visual effect and convey the message very clearly. For instance, blue & red blinking ones from the police vehicles demands the right of way when there's a continious chase. Several other emergency cars employ the blue LEDs in numerous diverse forms. As strobe lamps, they're strong portable light supplies when required. As fully-fledged light bars, they could be apparanelty visible in the heavy traffic areas. They also available in the form of elaborated lightbars with built-in traffic advisers, which could direct traffic to take diversion ahead and avoid the emergency area.The blue lights made of LEDs can also be very productive dash lights which are rather essential for each emergency cars. Dash lights not just employed for undercover police cars, but are also essential for the security of emergency cars. They can perform as tail lights while the emergency cars stop at the emergency area, making them noticeable to other automobiles.These days blue LED highbay lights can be easily noticed in many of the pavements of your country due to their powerful lighting features.LED lights can surpass any other type of lamps and use less power than other types of illumination. This makes them the 1st option for emergency vehicles, since they require to maintain the lights burning for many hours. Purchasing them from the appropriate retailer assure the longest life span.Reference:KY59-EB-251KY59-LRW5SM-GZHZ-1KY59-LRW5SM-HYJY-1-Z