Robots are extensively used in industries for their precision work and amount of work that one can obtain without any defects. In this paper we are using a gantry robot for as it does not occupy the floor space theref...
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Robots are extensively used in industries for their precision work and amount of work that one can obtain without any defects. In this paper we are using a gantry robot for as it does not occupy the floor space therefore reducing the distance for reachability of the parts and hence reducing unnecessary material for guide way. Robots work in strictly defined path and there is no or very little change in such systems in order to overcome this we are using a vision based control system to make the system dynamic in nature the images are picked by using a USB camera processed images of the object is transmitted via serial communication to the arduino Mega 2560 microcontroller and processed using pythons open source computer vision (Open CV) image to process the image captured by the USB camera to find the exact colour and to pick the object and sort it.
Grass maintenance has typically been done by hand or with fossil fuel-powered machinery, which presents efficiency and environmental concerns. The proposed system examines these difficulties by creating an autonomous ...
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Grass maintenance has typically been done by hand or with fossil fuel-powered machinery, which presents efficiency and environmental concerns. The proposed system examines these difficulties by creating an autonomous solar grass-cutting robot with a path-memorizing mechanism. Unlike traditional approaches, the innovative remedy improves lawn maintenance efficiency and sustainability by combining autonomous robotics and renewable energy sources. The robot uses advanced technology such as LiDAR, cameras, and neural networks to navigate and memorize optimal mowing patterns, increasing grass-cutting efficiency and coverage. Furthermore, using a solar power system with energy storage technology provides long-term operation without the need for fossil fuels. Compared to existing systems, the results show higher performance in terms of efficiency (95%), control complexity (10 signals), and grass-cutting quality (high uniformity and outstanding precision). The study represents an essential development in automated lawn maintenance technology, providing a viable alternative for effective and environmentally friendly grass management procedures.
Associative learning and memory, i.e., learning and remembering the associations between environmental stimuli, self-generated actions, and outcomes such as rewards or punishments, are critical for the well-being of a...
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Associative learning and memory, i.e., learning and remembering the associations between environmental stimuli, self-generated actions, and outcomes such as rewards or punishments, are critical for the well-being of animals. Hence, the neural mechanisms underlying these processes are extensively studied using behavioral tasks in laboratory animals. Traditionally, these tasks have been controlled using commercial hardware and software, which limits scalability and accessibility due to their cost. More recently, due to the revolution in microcontrollers or microcomputers, several general-purpose and open-source solutions have been advanced for controlling neuroscientific behavioral tasks. While these solutions have great strength due to their flexibility and general-purpose nature, for the same reasons, they suffer from some disadvantages including the need for considerable programming expertise, limited online visualization, or slower than optimal response latencies for any specific task. Here, to mitigate these concerns, we present an open-source behavior controller for associative learning and memory (B-CALM). B-CALM provides an integrated suite that can control a host of associative learning and memory behaviors. As proof of principle for its applicability, we show data from head-fixed mice learning Pavlovian conditioning, operant conditioning, discrimination learning, as well as a timing task and a choice task. These can be run directly from a user-friendly graphical user interface (GUI) written in MATLAB that controls many independently running arduino Mega microcontrollers in parallel (one per behavior box). In sum, B-CALM will enable researchers to execute a wide variety of associative learning and memory tasks in a scalable, accurate, and user-friendly manner.
Smart Bakery systems streamline various processes, from ingredient measurement to inventory management, reducing manual labor and human errors. In traditional bakery manual processes can lead to inefficiencies in ingr...
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ISBN:
(纸本)9783031640759;9783031640766
Smart Bakery systems streamline various processes, from ingredient measurement to inventory management, reducing manual labor and human errors. In traditional bakery manual processes can lead to inefficiencies in ingredient measurement, mixing, and baking. Smart bakery can Implement automated measuring systems and mixers to improve accuracy and consistency, reducing waste and ensuring uniform product quality. The Smart Bakery System in proposed system transforms traditional baking operations by merging technology and automation using the sense-think-act paradigm. The system improves efficiency and optimizes operations by using sensors, data analysis, and decision algorithms. The arduino microcontroller is at its heart, assuring precise ingredient measurements and consistency. The system's adoption improves bakery monitoring, ingredient precision, dough fermentation, and inventory management. By implementing the sense-think-act paradigm, bakeries may increase efficiency, reduce waste, and provide consistent, high-quality products. This technique boosts efficiency and profitability while establishing bakeries as trusted providers of high-quality items, matching consumer expectations and market demands.
Microbial infection is a major barrier to wound care and repair process of the cells. Various US-FDA-approved drugs and surgical procedures have been used for wound healing progression. However, the use of these pharm...
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Microbial infection is a major barrier to wound care and repair process of the cells. Various US-FDA-approved drugs and surgical procedures have been used for wound healing progression. However, the use of these pharmaceutical products has an associated toxicity and may produce harmful side effects. To overcome these problems, researchers worldwide are trying to develop non-invasive wound healing processes for wound care. We have developed a unique, tunable and arduino microcontroller-based extremely low-frequency (ELF) pulsed electromagnetic field (PEMF) device for accelerating the wound healing process by reducing the microbial infection. The layout and detailed design of the device are presented here. Simulations carried out for the fabrication of the Helmholtz coil used in the PEMF device are also presented. This system can provide the flexibility of dose substance by selecting the type and frequency of the waveform, exposure duration, and magnetic field strength. To test the efficacy of the device in the biological system, we have designed colony-forming unit assay in Staphylococcus aureus with an exposure to PEMF in the frequency range of 5-30 Hz for 90 min. The experiments have been conducted in controlled EMF environments as per the international standard exposure guidelines. The results show a 60% reduction in S. aureus CFU after 90 minutes of PEMF exposure, and hence, show that the designed system is very effective for wound care by reducing the microbial growth.
VI Based Smart Restaurant Management system provides a time-saving solution to automate the food ordering process, alerts the officials in case of any fire accidents, and offers the controller of the system to control...
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Currently, fuel stations are operated manually which requires a lot of time and staff to operate all the system. Customers are defrauded while dispensing the fuel by not delivering the exact amount of fuel, and during...
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Currently, fuel stations are operated manually which requires a lot of time and staff to operate all the system. Customers are defrauded while dispensing the fuel by not delivering the exact amount of fuel, and during payments, invalid notes may be exchanged. So, an automated fuel station can be a solution to all the above-stated problems. In this project, an automated fuel station is designed and implemented which can work 24/7 conveniently. An automated fuel station consists of an automated fuel dispensing system, automatic level indicator of the fuel in the storage tank, automatic vehicle washing system, smart lighting system, and automatic fire extinguisher. An automatic fuel dispensing system is realized by interfacing RFID, GSM module with arduino microcontroller. Level indication of the fuel in the storage tank is made automatic using an ultrasonic sensor. Vehicle washing is done by spraying water controlled automatically through the movable frame. Light intensity is automatically controlled based on the surrounding ambiance light and presence/absence of a vehicle. The accidental fire in the station is handled by an automatic fire extinguisher.
Vehicular Ad hoc NETworks (VANET) will likely play an essential role in the large-scale deployment of Intelligent Transportation Systems (ITS). On-Board Units (OBUs) in each vehicle collect information that can help d...
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ISBN:
(纸本)9798350320459
Vehicular Ad hoc NETworks (VANET) will likely play an essential role in the large-scale deployment of Intelligent Transportation Systems (ITS). On-Board Units (OBUs) in each vehicle collect information that can help drivers, such as alerts about accidents, traffic updates, etc. However, most proposed VANET schemes were based on simulation models, with only a few built hardware implementations. To our knowledge, there is no hardware implementation for the routing protocol in VANET. In this paper, we design and build a hardware implementation for OBU that uses the ad hoc On-Demand Distance Vector (AODV) routing protocol. Our implementation allows messages to disseminate to and from vehicles and roadside units (RSUs). The implemented OBU is efficient, simple, and at a low cost. Experimentation results show that the implemented method can transmit and receive messages between the source and destination in a timely manner.
As occurs with many other topics of pain curricula, lectures on pain neurophysiology are predominantly theoretical, and the practical experiences required to deliver that content to learners can be problematic regardi...
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As occurs with many other topics of pain curricula, lectures on pain neurophysiology are predominantly theoretical, and the practical experiences required to deliver that content to learners can be problematic regarding sustainability, logistics, and funding. Therefore, this study presents the development and testing of a microcontroller-based interactive tool to assist university-level pain neurophysiology teaching and facilitate a hands-on approach to exploring the functional connectivity of pain pathways. The proposed system consists of a sensing module that conveys electrical signals elicited by thermal and mechanical stimuli to an arduino Nano board. The latter acts as a processing module and contains a codified version of a Neuroid-based network model of the pain circuitry. Our prototype was tested during a lecture on pain neurophysiology attended by forty-seven undergraduate health sciences students, who were instructed to observe the neural responses to sensory stimulation while altering the pain circuitry's excitatory-inhibitory balance. We collected participants' opinions via a 3-point Likert-type scale with seventeen questions regarding the tool's composition, appropriateness, and theoretical foundation. Besides allowing students to explore the functional connectivity of pain pathways without the limitations posed by in-vivo or in-vitro models, the proposed tool achieved overall positive feedback among the surveyed.
In this study, an internet of things (IoT)-enabled fuzzy intelligent system is introduced for the remote monitoring, diagnosis, and prescription of treatment for patients with COVID-19. The main objective of the prese...
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In this study, an internet of things (IoT)-enabled fuzzy intelligent system is introduced for the remote monitoring, diagnosis, and prescription of treatment for patients with COVID-19. The main objective of the present study is to develop an integrated tool that combines IoT and fuzzy logic to provide timely healthcare and diagnosis within a smart framework. This system tracks patients' health by utilizing an arduino microcontroller, a small and affordable computer that reads data from various sensors, to gather data. Once collected, the data are processed, analyzed, and transmitted to a web page for remote access via an IoT-compatible Wi-Fi module. In cases of emergencies, such as abnormal blood pressure, cardiac issues, glucose levels, or temperature, immediate action can be taken to monitor the health of critical COVID-19 patients in isolation. The system employs fuzzy logic to recommend medical treatments for patients. Sudden changes in these medical conditions are remotely reported through a web page to healthcare providers, relatives, or friends. This intelligent system assists healthcare professionals in making informed decisions based on the patient's condition.
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