AI-Based Drone System for Medical Support in Congested Areas

Serving the needs of human beings is much more important to us. So, considering how to service the product or provide medicinal support is also very important to reach the destination. While supported by the local field-side forces, it is going through delays and getting affected by the delays in medical treatment. Why this failure in medical support? To avoid this delay, I have come up with a trend in technology in real life to send things like oxygen to the nearby hospital and make it emergency support on an urgent basis. At the same time, we can look for college and industry, food, and grocery items that we can utilize for the same methods. We can make it using AI technology used in the drone system and so by using different scales of sensors and cameras for recognition for bill service for auto-detection and bill payment as well. Nowadays, most people try to use their outside food purchases quickly, so we can get it via air drone easily without delay. This process is unintentionally free and GPS-based, with an advantage system to track the location. And confirmation of customer detection can help to unlock the lock-unlock the drone's locked body, get material, and lock the door once service is received. If there is any unwanted attack, it will be updated with the tracking system. There is an anti-drone system used here. This activity can be avoided. &nbsp

Harnessing the power of artificial intelligence to transform hearing healthcare and research

The advances in artificial intelligence that are transforming many fields have yet to make an impact in hearing. Hearing healthcare continues to rely on a labour-intensive service model that fails to provide access to the majority of those in need, while hearing research suffers from a lack of computational tools with the capacity to match the complexities of auditory processing. This Perspective is a call for the artificial intelligence and hearing communities to come together to bring about a technological revolution in hearing. We describe opportunities for rapid clinical impact through the application of existing technologies and propose directions for the development of new technologies to create true artificial auditory systems. There is an urgent need to push hearing towards a future in which artificial intelligence provides critical support for the testing of hypotheses, the development of therapies and the effective delivery of care worldwide

Grammarly in students' self-directed learning for writing skills: Advantages and disadvantages

Grammarly as an online grammar checker impacted technology development rapidly. This study aimed to look at the benefits and weaknesses of utilizing Grammarly to improve students' self-directed learning, particularly in writing skills. This study used a qualitative literature review. The data were collected from 10 relevant articles on Google Scholar with the keyword "Grammarly, self-directed Learning, and writing skills". The main issues addressed in this study were the benefits and the weaknesses of Grammarly in the period from 2018 to 2023. The result showed that Grammarly could enhance 'students' self-directed learning. It was because of the advantages offered by Grammarly that could check the correctness, clarity, engagement, delivery, plagiarism, and convenience. However the weaknesses of Grammarly; it needed the stability of electricity and an internet connection; it needed high-speed internet connectivity to access the complete feature; it was incomplete service of a free version, while it needed to pay to access the premium version. In conclusion, Grammarly enhanced the caliber of their work and inspired them to gauge their development. Therefore, Grammarly is recommended because it enhances 'students' self-directed learning in writing skills

Hardware Implementation of Deep Network Accelerators Towards Healthcare and Biomedical Applications

With the advent of dedicated Deep Learning (DL) accelerators and neuromorphic processors, new opportunities are emerging for applying deep and Spiking Neural Network (SNN) algorithms to healthcare and biomedical applications at the edge. This can facilitate the advancement of the medical Internet of Things (IoT) systems and Point of Care (PoC) devices. In this paper, we provide a tutorial describing how various technologies ranging from emerging memristive devices, to established Field Programmable Gate Arrays (FPGAs), and mature Complementary Metal Oxide Semiconductor (CMOS) technology can be used to develop efficient DL accelerators to solve a wide variety of diagnostic, pattern recognition, and signal processing problems in healthcare. Furthermore, we explore how spiking neuromorphic processors can complement their DL counterparts for processing biomedical signals. After providing the required background, we unify the sparsely distributed research on neural network and neuromorphic hardware implementations as applied to the healthcare domain. In addition, we benchmark various hardware platforms by performing a biomedical electromyography (EMG) signal processing task and drawing comparisons among them in terms of inference delay and energy. Finally, we provide our analysis of the field and share a perspective on the advantages, disadvantages, challenges, and opportunities that different accelerators and neuromorphic processors introduce to healthcare and biomedical domains. This paper can serve a large audience, ranging from nanoelectronics researchers, to biomedical and healthcare practitioners in grasping the fundamental interplay between hardware, algorithms, and clinical adoption of these tools, as we shed light on the future of deep networks and spiking neuromorphic processing systems as proponents for driving biomedical circuits and systems forward.Comment: Submitted to IEEE Transactions on Biomedical Circuits and Systems (21 pages, 10 figures, 5 tables