Take a Step Into the Future
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We gather information about futuristic inventions and create an awareness about them.
Robots that can read people’s minds, lab-grown food, new holograms, and 3D-printed eyes are all available . This is only the tip of the iceberg; to help you explore the most promising emerging technologies, we have put together a little about it.
Solar-Powered tiny E.V
Squad Mobility’s tiny solar-powered electric vehicle almost looks like a children’s toy. But the Solar City car is “surprisingly comfortable,” according to Engadget. In a sunny environment, the 6.6-foot-long car can go about 13 miles just on solar charge from its 250-watts-peak rooftop panel; it can also be plugged in like a regular E.V. With top speeds around 25 miles an hour, the car could be used to run errands or make a short commute, much like a golf cart in the city. The version at CES was a prototype; the company hopes to begin production next year and plans to market the car at $6,250.
Squad Solar Car
Recyclable ‘Water Batteries’ That Won’t Catch Fire
The RMIT University-led international research team and industry partners have created recyclable “water batteries” that are non-explosive and fire-prone.Because of its technological maturity, lithium-ion (Li-ion) energy storage dominates the market; nevertheless, because of safety issues regarding the volatile components inside, Li-ion energy storage is not suitable for large-scale grid energy storage.According to lead researcher Distinguished Professor Tianyi Ma, their batteries represent the state-of-the-art in the rapidly developing field of aqueous energy storage devices, with innovations that greatly enhance the lifespan and performance of the system.
Tianyi Ma, from the School of Science, stated, “What we design and manufacture are called aqueous metal-ion batteries — or we can call them water batteries.”
The group substitutes water for organic electrolytes, which allow current to pass between the
no fire
AI Approach Makes the Most of Sparse Sensor Data
An innovative approach to artificial intelligence (AI) enables reconstructing a broad field of data, such as overall ocean temperature, from a small number of field-deployable sensors using low-powered edge computing, with broad applications across industry, science and medicine.
The work, which builds on an AI model called Perceiver IO developed by Google, applies the techniques of natural-language models such as ChatGPT to the problem of reconstructing information about a broad area — such as the ocean — from relatively few measurements.The team realized the model would have broad application because of its efficiency. “Using fewer parameters and less memory requires fewer central processing unit cycles on the computer, so it runs faster on smaller computers,” said Co-Author Dan O’Malley.e, and medicineIn a demonstration of the real-world utility of the Senseiver, the team applied the model to a National Oceanic and Atmospheric Administration sea-surface-temperature dataset. The model was able to integrate a multitude of measurements taken over decades from satellites and sensors on ships. From these sparse point measurements, the model forecast temperatures across the entire body of the ocean, which provides information useful to global climate models.
Innovative AI Approach Makes the Most of Sparse Sensor Data
Portable Laser-Guided Robotic Metrology (PLGRM)
It is difficult to test airplane antennas since the best tests are conducted after the antenna is installed. Aircraft are frequently transported to anechoic antenna testing facilities, resulting in expensive, time-consuming, and lengthy lead times. Although there are portable options, testing fidelity is frequently degraded. The PLGRM system was created by NASA Glenn Research Center innovators to enable the characterization of an installed antenna in an airplane hangar.The PLGRM system is intended for remote, in-situ antenna measurements. A laser tracker and a cooperative robot arm mounted on a vertical lift are among the components; both are movable bases. These parts allow the robot to scan a surface that is bigger than its reach. In order to do this, the robot first gathers every point that is within its line of sight. After that, the system is relocated, and the robot is moved using the laser tracker in order to get new points before they are taken.The system employs time gating and pulsed measurements to eliminate undesired reflections while gathering data on antenna radiation. This lessens the need to completely enclose the test area with anechoic foam. Additionally, the system takes into account the potential for “dirty power,” which could exist at any host plant.
PLGRM
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