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A tactile sensor contains numerous sensitive areas, which enable it to measure multiple properties.
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Applied Technology Review | Wednesday, October 27, 2021
A tactile sensor is capable of detecting any physical interaction between the sensor and its environment.
FREMONT CA: Tactile sensors are capable of detecting specific objects, such as their presence. Additionally, it may determine the shape, location, and orientation of the component. The item in touch with the sensor is pressure, allowing for the determination of pressure distribution. This device can also inspect an item, such as texture monitoring, joint checking, or damage detection. Tactile sensors are capable of detecting a wide variety of stimuli; they can detect the existence of an object and can also generate a tactile image. A tactile sensor contains numerous sensitive areas, which enable it to measure multiple properties.
Tactile sensors are used in robotics, computer hardware, and security systems. The tactile sensor is also utilized extensively in the touchscreens of mobile phones and computers. Additionally, an elevator button is a tactile sensor; tactile imaging is employed in medical imaging. Tactile sensors may also be used to detect vibrations. Tactile sensors can also be utilized as pressure-sensitive devices because they contain pressure-sensitive films that determine the pressure.
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Tactile sensors come in a variety of configurations; some of them are:
Piezoelectric tactile sensor: When pressure is applied to a sensor element, it generates a voltage across it. This is called the piezoelectric effect. Voltage generation is proportional to applied pressure. There will be no requirement for an external sensor in this case. Durability and an extended dynamic range are two advantages of this type of sensor. Pressure measurements are possible.
Optical tactile sensor: There are two types of optical tactile sensors: intrinsic and extrinsic. In intrinsic sensors, the intensity of the light is adjusted by inserting an impediment into the light path. It has several advantages, including resistance to electromagnetic interference and a high resolution. There is minimal cabling necessary, and the processing circuitry can be located remotely from the sensor.
Capacitive tactile sensor: A capacitive sensor measures the difference in capacitance between two electrodes. This sort of capacitive sensor measures capacitance, which varies in response to applied pressure. The parallel plate capacitor's capacitance is proportional to the distance between the plates and their area, and the capacitance varies with load. This sort of sensor has the advantage of linear response and a wide dynamic range.
Magnetic tactile sensor: The magnetic tactile sensor operates in two modes: one is based on a change in flux density recorded using magneto-resistive devices, and the other is based on a change in magnetic coupling between windings caused by deformation of the magnetoelastic core. The sensor's features include its high sensitivity and lack of mechanical hysteresis.
Fiber optic communication is a crucial technology in the digital age, enabling faster and more reliable data transfer across various industries. However, it's often misunderstood, making it difficult for individuals and organizations to realize its potential fully.
Fiber Optic Fragility and Installation Challenges
The idea that fiber optic cables are brittle and prone to breaking is among the most pervasive fallacies about the technology. Fiber optic cables are built to last, even if they are composed of glass or plastic. Protective coatings on contemporary cables guard against damage from twisting, bending, and pulling. These safeguards guarantee that fiber optics can endure physical strain without seeing a decline in functionality.
Another myth suggests that fiber optic systems are difficult to install and maintain. In reality, fiber optics are easier to install than many assume, as the installation process is similar to that of traditional copper cables. Professional installers handle most of the work, and fiber optic systems require less maintenance due to their low failure rates and resilience against electrical interference. Fiber optics are also known for their longevity, making them a cost-effective solution over time.
Fiber Optics Are Too Expensive and only for Large-Scale Networks
Many people think fiber optics are too costly, especially when contrasted with copper cable. Even though the initial installation expenses may be larger, they are frequently outweighed by the long-term benefits. Fiber optics facilitate faster data transfer and lower maintenance costs by supporting higher data rates and handling enormous amounts of data. Fiber optics are becoming more affordable as manufacturing rises and technology advances, opening up the market to more homes and companies.
It is commonly thought that fiber optic cables are only suitable for large-scale networks or high-capacity applications. However, this technology is versatile and is used in a variety of environments, from home internet connections to local area networks in office buildings. Industries such as healthcare, manufacturing, and entertainment also rely on fiber optics for high-resolution imaging, real-time monitoring, and high-definition video broadcasting.
Fiber Optic Systems Are Too Complex to Use
Many people assume fiber optic technology is complicated and difficult to understand. However, once the basic principles are understood, fiber optics are no more complex than traditional copper wiring. They work by transmitting light through thin fibers, which are designed to carry light over long distances with minimal signal loss. With advancements in tools and installation techniques, fiber optics are now easier to work with, making the transition smoother for businesses and consumers alike. ...Read more
The increasing human population and demand for clothing are inevitable, but manufacturers must balance their efforts without overextending themselves. AI can help meet demand without exceeding supply, ensuring the sustainability of the planet's finite resources.
Apparel manufacturing uses AI in the following ways:
Enhancing the grading of materials: Although the human eye is a remarkable instrument, it is also fallible. Grading yarn and other base materials are one area where AI improves quality control (QC).
As a result of applying AI to this area, cost savings are realized, and the fundamental materials used in apparel manufacturing can be graded more precisely. Thus, AI can maintain a higher standard for materials than humans alone, thereby increasing the quality of finished garments.
Increasing the accuracy of final product inspections: A piece of fruit can even be discerned from its skin if it has been bruised through machine learning and computer vision.
Textiles and apparel manufacturing are equally inspiring applications. The condition and salability of newly made and previously worn garments can be assessed by algorithms coupled with specialty illumination systems. By measuring the amount of light that is transmitted and reflected, AI can determine whether a piece of fabric or a garment meets current quality standards at a glance.
The likelihood of Type I and Type II errors in a manufacturing setting was 17.8 percent and 29.8 percent, respectively. In the former case, inspectors miss real defects, while in the latter, false positives are made.
Apparel manufacturers can keep costs and errors down by using AI-powered automated inspection software. Identifying substandard yarn early in the manufacturing process can deliver value throughout the supply chain.
A tailor-made solution for the apparel industry: Artificial intelligence
Another area where AI can shine is sustainable and customized manufacturing. To facilitate cheaper and less resource-intensive custom clothing manufacturing, modern imaging techniques allow end-users to create 3D renderings of their bodies. ...Read more
The development of haptic feedback technology, which provides users with a simulated feeling of touch, heralds the beginning of a new revolution in user interaction. It has been used by every industry, particularly in relation to the transformation of human contact in comparison to robots and virtual surroundings. By using various frequencies or pressures, they replicate touch sensations while transferring mechanical forces, vibrations, or motions to the skin.
Advanced haptic systems also integrate sensors that detect user interactions, such as pressure or movement, to provide real-time feedback and create a more immersive experience. Smartphones and tablets use haptic feedback to enhance user interfaces, offering tactile responses for on-screen buttons, notifications, and typing. It improves usability and accessibility, especially for visually impaired users who rely on touch-based cues. Gaming controllers with haptic motors deliver precise vibrations to simulate in-game actions like explosions, vehicle movements, or weapon recoil, immersing players in the virtual world.
Haptic technology plays a pivotal role in creating lifelike simulations. Haptic gloves, suits, and controllers allow users to feel virtual objects, textures, and forces, enhancing the realism of VR experiences. For example, a user in a VR environment can feel the weight of a virtual object or the texture of a surface, making training simulations, gaming, and design more intuitive and engaging. It has vast implications for industries like healthcare, where VR simulations with haptic feedback train surgeons by replicating the sensation of operating on human tissue. The most prominent application of haptic technology is in consumer electronics.
The automotive industry is another sector leveraging haptic technology to improve safety and user experience. Touchscreen interfaces in modern vehicles use haptic feedback to provide tactile responses, allowing drivers to interact with controls without diverting their attention from the road. Advanced driver-assistance systems (ADAS) utilize haptic alerts, such as steering wheel or seat vibrations, to warn drivers of potential collisions or lane departures. Haptic technology is also making strides in prosthetics and assistive devices.
Advanced prosthetic limbs equipped with haptic sensors and actuators enable amputees to regain a sense of touch, allowing them to perceive pressure, temperature, and texture. It improves their ability to perform daily tasks and enhances their overall quality of life. While the benefits of haptic technology are vast, it also presents challenges. Developing precise and realistic haptic feedback systems requires advanced engineering, significant computational power, and energy-efficient components. ...Read more
Integrating IoT, blockchain technology, and deep learning models has revolutionized smart home automation, offering enhanced security, efficiency, and autonomy. IoT connects devices and appliances, generating vast data to optimize energy usage, improve security, and streamline daily routines. This integration promises a new era in managing household devices and systems.
Security vulnerabilities have become a significant concern with the proliferation of IoT devices. By leveraging blockchain's decentralized and immutable ledger, smart home systems can ensure the integrity and security of data exchanges between devices. Each transaction or data transfer is recorded tamper-proof across multiple nodes, eradicating the risk of a single point of failure or unauthorized access. Blockchain facilitates secure peer-to-peer transactions and automated smart contracts. Devices can autonomously interact and transact based on predefined conditions without intermediaries. Combining IoT connectivity, blockchain security, and deep learning intelligence can enhance homeowners' convenience, efficiency, and peace of mind.
A smart thermostat could adjust the temperature based on real-time weather data retrieved from decentralized sources, all executed through smart contracts recorded on the blockchain. Deep learning models further enhance the capabilities of IoT-based smart home automation by enabling predictive analytics and personalized experiences. These models can analyze historical data from IoT devices to identify patterns, preferences, and anomalies. A deep learning algorithm could learn the occupants' daily routines and adjust lighting, temperature, and other settings to optimize comfort and energy efficiency.
Deep learning-powered anomaly detection algorithms can identify unusual behavior patterns indicative of security breaches or malfunctions. For instance, if a security camera detects unusual movements while the occupants are away, the system can trigger alerts and take appropriate actions, such as notifying the homeowners or activating additional security measures. The critical challenge in implementing IoT-based smart home automation with blockchain and deep learning is interoperability and standardization. With various devices from different manufacturers operating on multiple protocols, ensuring seamless integration and compatibility can be complex.
Initiatives such as developing open-source protocols and industry standards aim to address these challenges and foster a more cohesive ecosystem. Privacy and data ownership are critical considerations when deploying smart home systems. With sensitive data being generated and exchanged among devices, ensuring user consent, data encryption, and transparent data handling practices are paramount. Blockchain-based identity management solutions can give users control over their data, allowing them to specify who can access it and under what conditions. Integrating IoT, blockchain, and deep learning models holds immense potential for revolutionizing smart home automation. ...Read more