Browse Topic: Internet of things (IoT)
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Measuring the volume of harvested material behind the machine can be beneficial for various agricultural operations, such as baling, dropping, material decomposition, cultivation, and seeding. This paper aims to investigate and determine the volume of material for use in various agricultural operations. This proposed methodology can help to predict the amount of residue available in the field, assess field readiness for the next production cycle, measure residue distribution, determine hay readiness for baling, and evaluate the quantity of hay present in the field, among other applications which would benefit the customer. Efficient post-harvest residue management is essential for sustainable agriculture. This paper presents an Automated Offboard System that leverages Remote Sensing, IoT, Image Processing, and Machine Learning/Deep Learning (ML/DL) to measure the volume of harvested material in real-time. The system integrates onboard cameras and satellite imagery to analyze the field
As a result of advancements to the Industrial Internet of Things (IIoT), companies across the globe are realizing the potential of smart manufacturing and connected business models. In fact, IoT connections are projected to more than double over the coming years: from 18 billion dollars in 2024 to 39.6 billion by 2033.
In Automobile manufacturing, maintaining the Quality of parts supplied by vendor is crucial & challenging. This paper introduces a digital tool designed to monitor trends for critical parameters of these parts in real-time. Utilizing Statistical Process Control (SPC) graphs, the tool continuously tracks Quality trend for critical parts and process parameters, predicting potential issues for proactive improvements even before parts are supplied. The tool integrates data from all Supplier partners across value chain into a single ecosystem, providing a comprehensive view of their performance and the parts they supply. Suppliers input data into a digital application, which is then analyzed in the cloud using SPC techniques to generate potential alerts for improvement. These alerts are automatically sent to both Suppliers and relevant personnel at the OEM, enabling proactive measures to address any Quality deviations. 100% data is visualized in an integrated dashboard which acts as a
The Defense Advanced Research Projects Agency (DARPA) pioneered satellites, the internet, drones, and human-computer interfaces. Now that work is enabling the next round of revolutionary technologies, including artificial intelligence (AI), edge and cloud computing, and the Internet of Military Things (IoMT) for a wide variety of Command, Control, Communications, Computers, Intelligence, Surveillance, and Reconnaissance (C4ISR) applications. Laptops and tablets are beneficiaries of yesterday's DARPA breakthroughs as well as enablers of today's and tomorrow's innovations. For example, ruggedized mobile PCs provide powerful new tools for asymmetric warfare by giving soldiers anytime, anywhere access to biometric information such as fingerprints and facial recognition. That information enables them to quickly determine whether a person in street clothes at a checkpoint is a civilian or combatant. This application also highlights the fundamental role of edge computing and the cloud for
Researchers have developed a multifunctional sensor based on semiconductor fibers that emulates the five human senses. Prof. Bonghoon Kim, department of robotics and mechatronics engineering of Daegu Gyeongbuk Institute of Science & Technology (DGIST), conducted the study in collaboration with Prof. Sangwook Kim at KAIST, Prof. Janghwan Kim at Ajou University, and Prof. Jiwoong Kim at Soongsil University. The technology developed in the study is expected to be utilized in fields such as wearables, Internet of Things (IoT), electronic devices, and soft robotics.
Advances in IoT and electronic technology are enabling more personalized, continuous medical care. People with medical conditions that require a high degree of monitoring and continuous medication infusion can now take advantage of wearable medicine injection devices to treat their problems. Wireless communication allows medical personnel to monitor and adjust the amount and flow rate of an individual’s medication. The small size of the injectors enables the individual to be active and not be burdened or limited by a line-powered instrument (see Figure 1).
Artificial Intelligence (AI) has emerged as a transformative force across various industries, revolutionizing processes and enhancing efficiency. In the automotive domain, AI's adaption has ushered in a new era of innovation and driving advancements across manufacturing, safety, and user experience. By leveraging AI technologies, the automotive industry is undergoing a significant transformation that is reshaping the way vehicles are manufactured, operated, and experienced. The benefits of AI-powered vehicles are not limited to their manufacturing, operation, and enhancing the user experience but also by integrating AI-powered vehicles with smart city infrastructure can unlock much more potential of the technology and can offer numerous advantages such as enhanced safety, efficiency, growth, and sustainability. Smart cities aim to create more livable, resilient, and inclusive communities by harnessing innovation through technologies like Internet of Things (IoT), devices, data
If you're just getting comfortable with Industry 4.0, which saw the beginnings of smart manufacturing, digitization and real-time decision-making in factories, a senior leader at Intel says the world is already moving on to Industry 5.0. What's Industry 5.0? A joint study by many researchers (link: Industry 5.0: A Survey on Enabling Technologies and Potential Applications (oulu.fi)) describes 5.0 as merging human creativity with intelligent and efficient machines to deliver customized products quickly. But it will take a lot of change and learning to get there.
The industrial internet of things (IIoT) is the nervous system in manufacturing facilities worldwide, with programmable logic controllers (PLCs) serving as its vital synapses. This digital neural network is transforming isolated machines into interconnected ecosystems of unprecedented intelligence and efficiency. PLCs have evolved from simple control devices into sophisticated nodes in a vast, responsive network.
Carbon-fiber structural batteries are not entirely new, but now Sinonus, a company spun out of Chalmers Technical University in Gothenburg, Sweden, is further developing the technology with carbon fibers that double as battery electrodes. The technology has already been demonstrated in low-power applications, and Sinonus will now develop it for use in a range of larger applications including, first, IoT devices and then drones, computers, electric vehicles and airplanes. By integrating the battery into carbon-fiber structures, Sinonus believes that an EV's weight could be reduced while the driving range could increase by as much as 70%. The carbon-fiber technology used by Sinonus originated at Oxeon, another Chalmers spin-off.
Manually checking the quality of components or products in industry is labor-intensive for employees and error-prone on top of that. The Fraunhofer Institute for Mechatronic Systems Design IEM is unveiling a solution that provides total versatility in this area. In an it’s OWL supported collaboration with Diebold Nixdorf and software specialist verlinked, Fraunhofer IEM has created a combination of collaborative robot (cobot), AI-based image analysis and IoT platform. The system frees employees from having to perform visual inspections and can be incorporated into all kinds of testing scenarios. The Fraunhofer researchers presented a demonstrator of the cobot/IoT platform at the 2024 Hannover Messe Trade Show in February.
The Internet of Military Things (IoMT), sometimes referred to as the Internet of Battlefield Things (IoBT), is gaining momentum for applications that improve defensive and battlefield capabilities. Like its civilian counterpart, the IoMT are networks of sensors, wearables, and imaging devices using edge and cloud computing to improve military operations and safety. However, battery failure in an IoMT device can have serious consequences in applications such as unmanned aerial drones that are used to patrol border areas or secure military bases. Battery life requirements are also high for the sensors and surveillance cameras that can be used to send real-time intelligence back to the command center for strategic decisions. Likewise, predictable battery life for IoMT devices used for vehicle management, battlefield supply chains, and weapon control are critical for efficient operations. Therefore, optimizing the device design and software to reduce power consumption and increase battery
In the increasingly connected and digital world, businesses are sprinting to integrate technological advancements into their corporate fabric. This is evident with the emerging concept of “digital twinning.” Digital twins are virtual representations of real-world objects or systems used to digitally model performance, identify inefficiencies, and design solutions. This helps improve the “real world” product, reduces costs, and increases efficiency. However, this replication of a physical entity in the digital space is not without its challenges. One of the challenges that will become increasingly prevalent is the processing, storing, and transmitting of Controlled Unclassified Information (CUI). If CUI is not protected properly, an idea to save time, money, and effort could result in the loss of critical data. The Department of Defense's (DoD) CUI Program website defines CUI as “government-created or owned unclassified information that allows for, or requires, safeguarding and
Following its annual report detailing the growing cybersecurity threats to vehicles, fleets, and the networks they rely on, Upstream Security announced the launch of a generative AI tool to enhance its ability to reduce the risk posted by global threats. Israel-based Upstream, which has a vehicle security operations center (VSOC) in Ann Arbor, Mich., monitors millions of connected vehicles and Internet of Things (IoT) devices and billions of API transactions monthly. Ocean AI is built into the company's detection and response platform, called M-XDR, enabling its analysts, as well as those from OEMs and IoT vendors, to efficiently detect threat patterns and automate investigations before prioritizing a response.
Internet of Thing (IoT) is the connecting network for applications like vehicles, smart devices, buildings etc., with the build in sensors to gather and share information for the user specific needs. The IoT platform offers prospects for a broad and direct integration of the manual world and the digital world by enabling things to be sensed and controlled remotely through existing network infrastructure. Self-contained programs can also be executed on it. This work projects on the integration of the IoT concept to the MOR-socket to manage, monitor and control the energy consumption of smart devices in a smart building. To achieve this, a simulation using Proteus 8.0 professional is made to obtain a virtual MOR-socket. This system is modeled with three prioritized loads of different current rating. The first priority load is the lighting load, second is the motor load and the final one is a load of higher current rating than the other two. The control and monitoring of these loads are
Scrap collection from any location is handled with mortal interference in several places and companies which may be extremely harmful or even dangerous to humanity. The demand for robotization has risen rapidly in recent years, owing to cutting-edge technologies that minimize manpower and threat-taking training directly or indirectly. The main objective of the paper is to study, analyze, investigate the main contribution of waste collecting by workers while cleaning in the Mechanical Industry. In order to ensure the safety of the workers during cleaning we had implemented the Automatic Trash Collecting Machine in the industry. For Fabricating the Trash collecting Machine first we had analyzed the problem in the industry and then we had started the free hand sketch of Trash Collecting Machine. Then the design work of Automatic Trash Collecting Machine is done in the modeling software Catia V5. Then the material selection for our model has been done. We had taken the mild steel for the
A method developed at NASA Johnson Space Center uses Radio Frequency Identification (RFID) interrogators for use with wearable active RFID sensor tags that can operate on ultra-low power. The technique uses a store-and-forward approach to manage the collection of data from RFID active tags even when they are not in range of an individual interrogator, as they move from the coverage area of one interrogator to the next. This allows the use of RFID active tags to transport sensor data in a highly complex environment where instantaneous access to an RFID interrogator cannot be guaranteed. Using this technique, an RFID active tag battery operational lifetime can be extended.
In the complex and quickly evolving 5G NTN landscape, simulating, emulating, and evaluating RF systems boosts mission success. Non-terrestrial networks (NTN) promise to finally eliminate coverage gaps across the globe. Beyond commercial applications, these fifth generation (5G) cellular networks create new use cases for critical communications and military operations. For such applications to effectively serve these mission-critical areas, however, their performance must be assured. With RF system measurement science, 5G NTN equipment developers, integrators, and network operators can reduce the time needed to create and deploy networks, using virtual engineering for first-pass success when committing to physical gear. Simulation and emulation support NTN exploration and testing, verifying current performance while supporting next-generation evolutions. 5G NTN draws many features from 5G terrestrial networks and faces many of the same challenges. Immediately apparent are the enormous
Recent events have shown that challenges to the global status quo can arise rapidly, making it imperative that military manufacturers remain agile and prepared to meet new circumstances as they emerge. As author Jim Pattison succinctly stated: “No matter what business you are in, there is change, and it's happening pretty quickly.” The challenges posed to military manufacturers include shorter design and production timetables, the need for greater efficiency in parts replacement and material usage, and an accelerated time to market; challenges that must be met with every technological tool available. The current revolution in manufacturing driven by digital technologies, is transforming the global production landscape. While artificial intelligence, augmented reality and the Industrial Internet of Things (IIoT) are increasing production efficiency and time to market, 3D scanning still has not been exploited by aerospace and defense manufacturers for its full potential to do the same.
I interviewed Tom Doyle, CEO and Founder of Aspinity, Pittsburgh, PA, about their analog machine learning chip, the AML100 analog machine learning processor, which is designed to bring artificial intelligence to always-on IoT endpoints at a fraction of the power used by digital chips.
Sensor-laden wearable systems hold great promise for wide range of applications including health monitoring, rehabilitation, electronic skin in robotics, environmental monitoring, Internet of Things (IoT), and more. Often these applications require cost-effective disposable sensors either for short-term or single measurements.
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