Abstract: Smoke detectors are critical devices for early fire detection and life-saving interventions. This research paper explores the application of Artificial Neural Networks (ANNs) in smoke detection systems. The study aims to develop a robust and accurate smoke detection model using ANNs. Surprisingly, the results indicate a 100% accuracy rate, suggesting promising potential for ANNs in enhancing smoke detection technology. However, this paper acknowledges the need for a comprehensive evaluation beyond accuracy. It discusses potential challenges, such (...) as overfitting, dataset size, and class imbalance, and presents strategies employed to address these issues. Additionally, the paper emphasizes the importance of alternative evaluation metrics, including precision, recall, and F1-score, to assess the model's performance comprehensively. Detailed information regarding the model architecture, data preprocessing, and hyperparameter tuning is provided to enhance the reproducibility of the research. The study also discusses ethical considerations and the implications of false positives and false negatives in smoke detection applications. While achieving 100% accuracy is a notable accomplishment, this paper calls for cautious interpretation and further validation in real-world settings. It concludes by highlighting areas for future research and improvement in smoke detection technology, emphasizing the need for practical deployment and the reduction of false alarms. (shrink)

Accident occur as public do not follow the traffic rules, like not maintaining a proper braking distance between two vehicles, they also fail to follow the traffic signals when it is ‘RED’, also due to the fast life everyone is in a hurry of reaching the destination in time. In this paper, propose system implementing an IOT based Vehicle Tracking, Accident Detection, Accident Avoidance, Drunk Driver Detection and Fire Detection System. This system using Vibration sensor, Ultrasonic sensor, Alcohol Sensor, (...) class='Hi'>Smoke Sensor, Web camera, GPS, Arduino Microcontroller, Android App. Our application focus on to providing them more convenience with vehicle safety. It provides Real-time vehicle location information also integrated Google Maps in the application. (shrink)

The proposed model in this paper employs different integrated detectors, such as heat, smoke, and flame. The signals from those detectors go through the system algorithm to check the fire's potentiality and then broadcast the predicted result to various parties using GSM modem associated with the GSM network system. The system uses various sensors to detect fire, smoke, and gas, then transmits the message using GSM module. After the message, send by the module the help arrives in (...) 15 minutes. The system is associated with water pump and a sprinkler. The Water system is associated with a water tank and a sprinkler. The water tank uses a Ultrasonic sensor to monitor the level of water level in the tank for refilling the water tank. Once fire is detected, it automatically sends the emergency message and sprinkles the water. (shrink)

We describe a prototype ontology-driven information system (ODIS) that exploits what we call Portion of Reality (POR) representations. The system takes both sensor data and natural language text as inputs and composes on this basis logically structured POR assertions. The goal of our prototype is to represent both natural language and sensor data within a single framework that is able to support both axiomatic reasoning and computation. In addition, the framework should be capable of discovering and representing new kinds of (...) situations and thematic roles, (e.g., roles such as agent, patient and instrument), based on new compositions of existing representations. We applied our prototype in an intelligence analysis use case to test the hypothesis that a framework of this sort can produce usefully structured information from combined natural language and sensor data inputs. We further tested our hypothesis by adding an enhanced US Air Force ontology framework to our ODIS in order to (1) process a collection of sensor data, intel reports, and mission plans; (2) build composite POR representations from these data; and (3) machine analyze the fused results to infer mission threats. (shrink)

Wireless Sensors Network is a novel field shows tremendous application potential. To monitor the environmental parameters of high-tech polyhouse the Wireless Sensors Network (WSN) is developed. The heart of this ubiquitous field is the Wireless Sensor Node. Moreover, the field of microcontroller based embedded technology is innovative and more reliable. Therefore, based on an embedded technology and the RF module Zigbee a wireless senor node is designed about highly promising AVR ATmega8L microcontroller and implemented for WSN development. Recently, (...) the modern agriculturists are demanding sophisticated instrumentation for measurement and control of environmental parameters of the polyhouse. To enhance crop yield one has to provide controlled environment to the crop. The humidity is important parameter, which plays vital role on the crop yield. Therefore, a Wireless Sensors Network (WSN) is designed and implemented for monitoring of humidity of polyhouse and the results of implementation are interpreted in this paper. (shrink)

Wildfires have become an increasing global threat to public health and quality of life. Many countries employ air quality monitoring and reporting systems to mitigate health risks associated with air pollution, including wildfire smoke. This study investigates the factors influencing individuals’ sensitivity to air quality information, specifically their likelihood of reducing or ceasing outdoor activities in response to air quality ratings, with a focus on wildfire smoke exposure in the western United States. Using the Bayesian Mindsponge Framework (BMF) (...) analytics, the study analyzed data from 2,237 participants in the Boise Metropolitan Area of Idaho and Boise State University. The findings reveal that women, older individuals, and those with higher educational levels are more likely to reduce outdoor activities at lower unhealthy AQI levels (the lowest being ‘good air quality,’ while the highest being ‘hazardous air quality’), while individuals with higher incomes are less responsive. Women and older adults, in particular, are even more likely to eliminate all outdoor activities. Additionally, individuals who perceive wildfire smoke as more severe than other natural disasters are more inclined to reduce or eliminate outdoor activities at lower unhealthy air quality levels. Experiences of wildfire smoke-related illness—either personally or within their households—further amplify this effect. These findings highlight the importance of localized, context-specific approaches to AQI dissemination and wildfire smoke risk communication to build resilience and safeguard public health in the face of escalating wildfire challenges driven by climate change. (shrink)

Abstract: This research paper presents the development and evaluation of a neural network-based model for predicting fire alarms in smoke detection systems. Using a dataset from Kaggle containing 15 features and 3487 samples, we trained and validated a neural network with a three-layer architecture. The model achieved an accuracy of 100% and an average error of 0.0000003. Additionally, we identified the most influential features in predicting fire alarms.

Some cognitive processes appear to have “phenomenal” properties that are directly revealed to the subject and not determined by physical properties. I suggest that the source of this appearance is the method by which our brain processes sensory information. The appearance is an illusion. Nonetheless, we are not mistaken when we judge that people sometimes fee lpain.

This study employs a neural network to analyze the connection between smoking, drinking, and various health-related factors using a dataset of 5148 samples. Achieving an impressive 99.94% accuracy and an average training error of 0.0016, the model identifies influential factors such as serum aminotransferases, serum creatinine, sex, weight, and triglyceride levels. These findings enhance our understanding of lifestyle choices and their impact on health. This research underscores the potential of machine learning in studying complex health phenomena.

The antenna is considered as the primary means of absorbing electromagnetic waves in space and has its own engineering knowledge, which is very developed and extensive. In general, in order to receive the electromagnetic wave in space, the dimensions of the antenna must be in the order of the size of the input wavelength to its surface. Due to the very low dimensions of nano-sensors, nano-antennas need a very high operating frequency to be usable. The use of graphene greatly (...) helps to solve this problem. Wave propagation velocities in CNTs and GNRs can be up to 100 times slower than vacuum velocities, depending on the physical structure, temperature and energy. Accordingly, the resonant frequency of graphene-based nano-antennas can be twice as low as (nano-carbon) nano-antennas. (shrink)

Background: Tuberculosis is among the major causes of illness and death worldwide especially in Asia. Smoking is associated with recurrent tuberculosis and its related mortality. Also, it could affect clinical manifestations, bacteriological conversion and outcome of treatment. This study aimed to evaluate the pattern of tobacco smoking, history of previous quit attempts and attitude towards quitting in tuberculosis patients. Materials and Methods: It was a cross-sectional study done amongst tuberculosis patients presented to DOTS corner of Rajshahi Medical College Hospital. 315 (...) patients entered the study as "First Come First Serve". Selfreported questionnaires were designed according to the standard questionnaires of smoking pattern. Results: Sixty one percent (61%) patients (n=192) were smoker before the diagnosis of tuberculosis. 51.1% were current smokers at the time of interview and were continuing smoking after the diagnosis of tuberculosis. Only 10.2% discontinued smoking after diagnosis. 68.2% smokes less than 10 cigarettes per day. 53.1% was between 31-50 age group. 21-30 is the commonest age group (62%) to start smoking is and 66.1% smoked less than 10 years before diagnosis. To reduce stress was the most common cause to continue smoking (48.9%). 71.9% smokers showed keen interest to stop smoking. Conclusion: Considering the prevalence of smoking in tuberculosis patients, evaluation of tobacco smoking status in such patients and motivating them to quit smoking could be considered as important steps in their treatment process. (shrink)

Background: Smart sensors have been developed as diagnostic tools for rehabilitation to cover an increasing number of geriatric patients. They promise to enable an objective assessment of complex movement patterns. -/- Objective: This research aimed to identify and analyze the conflicting ethical values associated with smart sensors in geriatric rehabilitation and provide ethical guidance on the best use of smart sensors to all stakeholders, including technology developers, health professionals, patients, and health authorities. -/- Methods: On the basis (...) of a systematic literature search of the scientific databases PubMed and ScienceDirect, we conducted a qualitative document analysis to identify evidence-based practical implications of ethical relevance. We included 33 articles in the analysis. The practical implications were extracted inductively. Finally, we carried out an ethical analysis based on the 4 principles of biomedical ethics: autonomy, beneficence, nonmaleficence, and justice. The results are reported in categories based on these 4 principles. -/- Results: We identified 8 conflicting aims for using smart sensors. Gains in autonomy come at the cost of patient privacy. Smart sensors at home increase the independence of patients but may reduce social interactions. Independent measurements performed by patients may result in lower diagnostic accuracy. Although smart sensors could provide cost-effective and high-quality diagnostics for most patients, minorities could end up with suboptimal treatment owing to their underrepresentation in training data and studies. This could lead to algorithmic biases that would not be recognized by medical professionals when treating patients. -/- Conclusions: The application of smart sensors has the potential to improve the rehabilitation of geriatric patients in several ways. It is important that patients do not have to choose between autonomy and privacy and are well informed about the insights that can be gained from the data. Smart sensors should support and not replace interactions with medical professionals. Patients and medical professionals should be educated about the correct application and the limitations of smart sensors. Smart sensors should include an adequate representation of minorities in their training data and should be covered by health insurance to guarantee fair access. (shrink)

Artificial Intelligence and Sensor Technologies the Future of Special Education for Students with Intellectual and Developmental Disabilities.

Considerations of objective-value freedom and status freedom do impose constraints on policies that restrict access to cigarettes. As to the objective-value freedom, something of value is lost when anti-alcohol policies lead to pub closures interfering with valued life styles, and a similar, though weaker, argument can be made for cigarettes. As to status freedom, non-arbitrariness requires consultation with vulnerable populations to learn what might aid them with smoking cessation.

Advances in immunotherapy pave the way for vaccines that target not only infections, but also unhealthy behaviors such as smoking. A nicotine vaccine that eliminates the pleasure associated with smoking could potentially be used to prevent children from adopting this addictive and dangerous behavior. This paper offers an ethical analysis of such vaccines. We argue that it would be permissible for parents to give their child a nicotine vaccine if the following conditions are met: (1) the vaccine is expected to (...) result in a net benefit to each individual vaccinated, (2) the expected harms from the side effects of the vaccine are lower than the non-voluntary harms of smoking, and (3) there are no less manipulative methods available that are as effective at preventing smoking initiation. Finally, we show how the framework developed here could be used to analyze the ethics of other chemical interventions designed to modify children’s behavior. (shrink)

The advance of scientific approaches to life has recorded a plethora of successes as well as failures. Man being at the center of its experiment is tossed toe and fro by the result of its inquiry. Predictions are that in the nearest time, humanity might be living absolutely under the directives of Technology based on Artificial intelligence. At present, Technology based on Artificial Intelligence is quickly finding its way into various areas of life including health and social services. This spread (...) and or interplay connotes the relinquishing of health responsibilities from man to sensor technology as well as dependency on the data and result of this technology. This effort questions this unethical dependency as well as raises moral issues associated with the use of Technology base on artificial intelligence on psychiatric patient. It dabbles into medical values such as; autonomy of the patient cum consent, Kantian universal principle and its implication to implementing the universal usage of technology in mental health care services, and so on. The work of Patricia A. Arean (2016) titled Mobile Technology for Mental Health Assessment gave an in-depth analysis of the available approaches, doting advantages of sensor technology on psychiatric patient. The paper applied the analytic, descriptive and prescriptive method of philosophy to achieve its objective. To this end, it is in the view of this work imperative for the mental-medical community to consider reflectively these issues and the philosophic recommendations provided herein. (shrink)

Accurate assessment and comprehension of smoking behavior are pivotal for elucidating associated health risks and formulating effective public health strategies. In this study, we introduce an innovative approach to predict and analyze smoking prevalence using an artificial neural network (ANN) model. Leveraging a comprehensive dataset spanning multiple years and geographic regions, our model incorporates various features, including demographic data, economic indicators, and tobacco control policies. This research investigates smoking trends with a specific focus on gender-based analyses. These findings are pivotal (...) for enhancing public health initiatives aimed at mitigating tobacco use, assessing associated health risks, and mitigating smoking-related diseases. (shrink)

Multi sensor data fusion allows large scale deployments for environmental monitoring applications especially in the areas like homes, other buildings and infrastructures and industries. In such areas early fire detection is of great importance as the consequences of a fire are catastrophic. This project predicts the possibility of catching fire using a multi-sensor scheme of data fusion to enhance the performance of the early fire detection process by detecting the concentration of inflammable gases in the atmosphere and by measuring the (...) atmospheric temperature. (shrink)

In the early part of the paper, I attempt to explain a dispute between two parties who endorse the compositionality of language but disagree about its implications: Paul Horwich, and Jerry Fodor and Ernest Lepore. In the remainder of the paper, I challenge the thesis on which they are agreed, that compositionality can be taken for granted. I suggest that it is not clear what compositionality involves nor whether it obtains. I consider some kinds of apparent counterexamples, and compositionalist responses (...) to them in terms of covert indexicality and unspecific meanings. I argue that the last option is the best for most of the cases I consider. I conclude by stressing, as against Horwich and Fodor and Lepore, that the appropriate question concerns the extent to which compositionality obtains in a natural language, rather than whether it obtains or not, so that the answer is essentially messy, requiring detailed consideration of a wide range of examples. (shrink)

—Industrial networks are increasingly based on open protocols and platforms that are also employed in the IT industry and Internet background. Most of the industries use wireless networks for communicating information and data, due to high cable cost. Since, the wireless networks are insecure, it is essential to secure the critical information and data during transmission. The data that transmitted is intercepted by eavesdropper can be predicted by secrecy capacity. The secrecy capacity is the difference between channel capacity of main (...) link and wiretap link of wireless transmission. When the secrecy capacity gets fades, then it is known that transmitted data is intercepted. In the event, of applying optimal sensor scheduling scheme a sensor with highest secrecy capacity is chosen and data is transmitted. It is followed with cooperative localization algorithm to enhance nodes, predict and maintain power of each sensor nodes. Through localization algorithm best sensor nodes are get predicted for transmission. Moreover, RC4 encryption and decryption algorithm is enhanced for data while transmission. This will enable protection to data to an extent. Also, an asymptotic intercept probability analysis is performed to provide an imminent into the impact of the sensor scheduling on the wireless security. (shrink)

The data collected by these sensors are transmitted to a centralized system where optimization algorithms, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), are applied to optimize sensor placement, data transmission, and processing efficiency. This ensures accurate, real-time pollution monitoring and data analysis, providing actionable insights for policymakers, environmental agencies, and the general public. The system's performance is evaluated through simulations and real-world experiments, demonstrating its capability to deliver reliable and timely pollution data. Future (...) work will explore the integration of machine learning techniques for predictive analytics and the expansion of the sensor network for broader coverage. (shrink)

The data collected by these sensors are transmitted to a centralized system where optimization algorithms, such as Genetic Algorithms (GA), Particle Swarm Optimization (PSO), and Simulated Annealing (SA), are applied to optimize sensor placement, data transmission, and processing efficiency. This ensures accurate, real-time pollution monitoring and data analysis, providing actionable insights for policymakers, environmental agencies, and the general public. The system's performance is evaluated through simulations and real-world experiments, demonstrating its capability to deliver reliable and timely pollution data. Future (...) work will explore the integration of machine learning techniques for predictive analytics and the expansion of the sensor network for broader coverage. (shrink)

Underwater Wireless Sensor Networks (UWSNs) are pivotal for various applications, including oceanographic data collection, environmental monitoring, and naval operations. However, the harsh underwater environment poses challenges in designing efficient routing protocols, especially concerning energy consumption and data transmission reliability. This paper proposes an optimized depth-based routing protocol for energy-aware data transmission in UWSNs, focusing on minimizing energy usage while ensuring robust data delivery. The protocol dynamically adjusts transmission power based on node depth and residual energy, reducing communication overhead and prolonging (...) network lifetime. (shrink)

New technologies such as smart sensors improve rehabilitation processes and thereby increase older adults’ capabilities to participate in social life, leading to direct physical and mental health benefits. Wearable smart sensors for home use have the additional advantage of monitoring day-to-day activities and thereby identifying rehabilitation progress and needs. However, identifying and selecting rehabilitation priorities is ethically challenging because physicians, therapists, and caregivers may impose their own personal values leading to paternalism. Therefore, we develop a discussion template consisting (...) of a series of adaptable questions for the patient–physician encounter based on the capability approach. The goal is to improve geriatric rehabilitation and thereby increase participation in social life and well-being. To achieve this goal, we first analyzed what is considered important for participation on basis of the capability approach, human rights, and ethics of care. Second, we conducted an ethical analysis of each of the four identified dimensions of participation: political, economic, socio-cultural, and care. To improve compliance with rehabilitation measures, health professionals must align rehabilitation measures in an open dialogue with the patient’s aspiration for participation in each dimension. A discussion template based on the capability approach allows for a proactive approach in patient information and stimulates a critical assessment of treatment alternatives while reducing the risk of imposing personal values. (shrink)

Research on the folk psychology of free will suggests that people believe free will is incompatible with determinism and that human decision-making cannot be exhaustively characterized by physical processes. Some suggest that certain elements of Western cultural history, especially Christianity, have helped to entrench these beliefs in the folk conceptual economy. Thus, on the basis of this explanation, one should expect to find three things: (1) a significant correlation between belief in dualism and belief in free will, (2) that people (...) with predominantly incompatibilist commitments are likely to exhibit stronger dualist beliefs than people with predominantly compatibilist commitments, and (3) people who self-identify as Christians are more likely to be dualists and incompatibilists than people who do not self-identify as Christians. We present the results of two studies (n = 378) that challenge two of these expectations. While we do find a significant correlation between belief in dualism and belief in free will, we found no significant difference in dualist tendencies between compatibilists and incompatibilists. Moreover, we found that self-identifying as Christian did not significantly predict preference for a particular metaphysical conception of free will. This calls into question assumptions about the relationship between beliefs about free will, dualism, and Christianity. (shrink)

This paper presents Kaizen, a sensor-driven mobile application developed to track and encourage physical activity through goal-setting, gamification, and personalized diet recommendations, tailored specifically to the Indian dietary context. Kaizen uses accelerometers, GPS, and gyroscopes to monitor user movements in real-time, offering an alternative to traditional fitness tracking methods that often lack cultural dietary considerations or personalized motivation systems. With a ranking system and interactive challenges, Kaizen aims to enhance user engagement and promote continuous improvement in health and fitness. Early (...) user testing indicates high responsiveness and motivational efficacy, suggesting broad potential for adoption and further development. (shrink)

This study presents a neural network-based model for predicting smoke potential in a specific area using a Kaggle-derived dataset with 15 environmental features and 62,631 samples. Our five-layer neural network achieved an accuracy of 89.14% and an average error of 0.000715, demonstrating its effectiveness. Key influential features, including temperature, humidity, crude ethanol, pressure, NC1.0, NC2.5, SCNT, and PM2.5, were identified, providing insights into smoke occurrence. This research aids in proactive smoke mitigation and public health protection. The model's (...) accuracy and feature analysis empower decision-makers, with potential applications in real-time smoke event monitoring and preparedness strategies. This work contributes to the field of air quality forecasting and environmental stewardship, offering a data-driven approach to address smoke-related challenges and enhance community well-being. (shrink)

The current study is conducted to examine the following research question: 1) Who were the people who had no access to wildfire smoke notifications during the smoke event in the summer of 2018 in the Boise Metropolitan Area in Idaho? 2) Who were the people who were not familiar with the air quality rating system?

Underwater Wireless Sensor Networks (UWSNs) are pivotal for various applications, including oceanographic data collection, environmental monitoring, and naval operations. However, the harsh underwater environment poses challenges in designing efficient routing protocols, especially concerning energy consumption and data transmission reliability. This paper proposes an optimized depth-based routing protocol for energy-aware data transmission in UWSNs, focusing on minimizing energy usage while ensuring robust data delivery. The protocol dynamically adjusts transmission power based on node depth and residual energy, reducing communication overhead and prolonging (...) network lifetime. (shrink)

Perioperative staff are frequently exposed to surgical smoke or plume created by using heat-generating devices like diathermy and lasers. This is a concern due to mounting evidence that this exposure can be harmful with no safe level of exposure yet identified. First, I briefly summarise the problem posed by surgical smoke exposure and highlight that many healthcare organisations are not sufficiently satisfying their legal and ethical responsibilities to protect their staff from potential harm. Second, I explore the ethical (...) case for compulsory smoke evacuation systems using the principlist framework and its four ethical principles – autonomy, beneficence, nonmaleficence, and justice. I then consider some objections and argue that surgical smoke evacuation systems – when indicated – should be made compulsory. (shrink)

t: Wireless Sensor Networks (WSNs) have become increasingly prevalent in various applications, ranging from environmental monitoring to smart cities. However, the limited energy resources of sensor nodes pose significant challenges in maintaining network longevity and data transmission efficiency. Duty-cycled WSNs, where sensor nodes alternate between active and sleep states to conserve energy, offer a solution to these challenges but introduce new complexities in data transmission.

In the boiling atmosphere of the Vietnamese stock market, it is time to mention a few misconceptions from Vietnamese investors. (Vietnam Investment Review, 27-6-2007).

Abstract: The main objective is to design a line follower robot is to carry products in the manufacturing process in industries. In this paper, we mainly focused on the design to work the line follower efficiently with lighter weight. The line follower robot designed with 5 sensors to make the robot move in even complex paths. This paper discussed the mechanical and technical issues with the line follower robot and applications in various fields. In the working model, we used (...) black detector infrared sensors So that speed of response of the robot is high. This paper gives an brief idea about all the components used to prepare a line follower robot. (shrink)

Abstract—Traffic clog is a serious issue in the majority of the urban areas over the world and it has turned into a bad dream for the residents. It is brought about by postponement in flag, improper planning of traffic flagging and so on. The postponement of traffic light is hard coded and it doesn't depend on traffic. In this manner for streamlining traffic control, there is an expanding request in precise snappy programmed framework. This paper is intended to build up (...) a thickness based powerful traffic flag control. The flag timing changes naturally on detecting the traffic thickness at the junction. The microcontroller utilized in this undertaking is ARDUINO. The framework contains IR sensors (transmitter and collector) which will be mounted. It gets initiated and gets the flag as the vehicles passes near to it. (shrink)

A ventilator is a device that provides cool air by moving the air in or out of the lungs, inhaling a patient who is not fit to smell, or breathing properly. In this paper, a resistive chest belt sensorbased mechanical ventilator is designed to provide the COVID-19 patient with the volume of air you need to deliver with the expansion of the patient's chest in need of more air. The resistive band sensor senses the expansion of the patient's chest and (...) controls the solenoid valve attached to the oxygen compressor. The function of the respirator is tested with the MATLAB / Simulink tool with the help of a Proportional Integral Derivative (PID) Controller and a promising result obtained. (shrink)

In this study, an automatic heat dispel system for DINGSON Biscuit Oven have been designed and simulated using Proteus program successfully. This system uses thermocouple temperature sensor to sense the oven temperature and automatically open and close the dispel system. The temperature in which the dispel open and close can be adjusted any time the operator needs to adjust it.

The protocol dynamically adjusts transmission power based on node depth and residual energy, reducing communication overhead and prolonging network lifetime. The proposed methodology employs a multi-step approach, starting with the initialization phase, where nodes calculate their depth and energy levels. Following this, a depth-based clustering mechanism organizes nodes into clusters, allowing more efficient data aggregation. The routing process then prioritizes nodes with higher energy levels, reducing premature node failure. A novel energy-aware transmission algorithm ensures that data packets are transmitted over (...) the most energy-efficient paths, thus extending the overall network longevity. Simulation results demonstrate that the proposed protocol achieves significant improvements in energy consumption, data transmission reliability, and network lifetime compared to traditional methods. The conclusion discusses the potential future enhancements, including adaptive algorithms that can further reduce energy consumption in large-scale UWSNs. (shrink)

Note: Many types of nanosensors are designed using CP nanomaterials for nanobiological applications. (Conductive surface) The oxidation of conductive polymeric materials is easily altered by redox mechanisms, and the charge transfer properties of these materials are affected by structural parameters, such as diameter and dimensions. CP materials are able to provide sensitive and rapid responses to specific biological and chemical species. Techniques such as chemical polymerization are often used to make CP nanomaterials. Manufacturing strategies can be divided into three categories: (...) hard mold synthesis, soft mold synthesis, and mold-free synthesis. The most widely used conductive polymers in nanosensors are nanomaterials made from CP due to their unique chemical and electrical properties resulting from the properties of their pie-electron nanosystem. Many modeling and functionalization technologies are being developed to control the location, distribution, amount, or structure and orientation of biological nanomolecules at the nanomaterial level. Therefore, our level of contact between biological nanomolecules and nanomaterials is of particular importance in countless applications. Covalent and non-covalent modifications are two general methods for coupling biological molecules and CP nanomaterials. Covalent functionalization is a chemical process in which a strong bond or relationship between nanomaterials and biological molecules is formed. In many cases, surface chemical modifications are required to create active groups that can bind to biomolecules. Unlike covalent functionalization, in the non-covalent method, nanomolecules can be removed without destroying the geometric and electronic structure on the surface. Nanomaterials are formed. Conclusion : The large surface-to-volume ratio in nanostructures and the high potential for signal amplification provide ideal conditions for marking and detecting biological elements in the structure of nanosensors. (shrink)

Optimization algorithms such as Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) are employed to determine the optimal aggregation and transmission schedules, taking into account factors such as network topology, node energy levels, and data urgency. The proposed approach is validated through extensive simulations, demonstrating significant improvements in energy consumption, packet delivery ratio, and overall network performance. The results suggest that the optimized aggregated packet transmission method can effectively extend the lifespan of duty-cycled WSNs while ensuring reliable data communication. Future (...) work will explore the integration of machine learning techniques for adaptive scheduling and the application of the proposed method to heterogeneous WSNs. (shrink)

Directed Diffusion (DD) uses data aggregation to suppress data overhead however there is no guarantee that paths from nearby sources join after a few hops. In this paper, an efficient data-gathering protocol (EDAP) is proposed to address this problem by using a Virtual Sink (VS) node nearby the sources, which plays the role of sink node and broadcasts local interest messages and routes gathered data toward destination. Also, multiple paths are constructed between VS and the sink node, which leads to (...) load-balancing, and increase in the lifetime of the network. Simulation results show that in EDAP a significant amount of energy can be saved and the network lifetime will be increased considerably. (shrink)

Representing the kinetic state of a patient (posture, motion, and activity) during vital sign measurement is an important part of continuous monitoring applications, especially remote monitoring applications. In contextualized vital sign representation, the measurement result is presented in conjunction with salient measurement context metadata. We present an automated annotation system for vital sign measurements that uses ontologies from the Open Biomedical Ontology Foundry (OBO Foundry) to represent the patient’s kinetic state at the time of measurement. The annotation system is applied (...) to data generated by a wearable personal status monitoring (PSM) device. We demonstrate how annotated PSM data can be queried for contextualized vital signs as well as sensor algorithm configuration parameters. (shrink)

Underwater Wireless Sensor Networks (UWSNs) have emerged as a critical tool for various marine applications, such as underwater surveillance, oceanographic data collection, pollution monitoring, and resource exploration. These networks consist of a group of sensor nodes deployed underwater to monitor and collect data, which are then transmitted to a surface station for analysis.

Starting from a philosophical perspective, which states that the living structures are actually a combination between matter and information, this article presents the results on an analysis of the bipolar information-matter structure of the human organism, distinguishing three fundamental circuits for its survival, which demonstrates and supports this statement, as a base for further development of the informational model of consciousness to a general informational model of the human organism. For this, it was examined the Informational System of the Human (...) Body and its components from the perspective of the physics/information/neurosciences concepts, showing specific functions of each of them, highlighting the correspondence of these centers with brain support areas and with their projections in consciousness, which are: Center of Acquisition and Storing of Information (CASI) reflected in consciousness as memory, Center of Decision and Command (CDC) (decision), Info-Emotional Center (IES) (emotions), Maintenance Informational System (MIS) (personal status), Genetic Transmission System (GTS) (associativity/genetic transmission) and Info Genetic Generator (IGG) related by the body development and inherited behaviors. The Info Connection (IC), detected in consciousness as trust and confidence can explain the Near-Death Experiences (NDEs) and associated phenomena. This connection is antientropic and informational, because from the multitude of uncertain possibilities is selected a certain one, helping/supporting the survival and life. The human body appears therefore as a bipolar structure, connected to two poles: information and matter. It is argued that the survival, which is the main objective of the organism, is complied in three main ways, by means of: (i) the reactive operation for adaptation by attitude; (ii) the info-genetic integration of information by epigenetic processes and genetic transmission of information for species survival, both circuits (i) and (ii) being associated to the information pole; (iii) maintenance of the material body (defined as informed matter) and its functions, associated to the matter pole of the organism. It results therefore that the informational system of the human body is supported by seven informational circuits formed by the neuro-connections between the specific zones of the brain corresponding to the informational subsystems, the cognitive centers, the sensors, transducers and execution (motor/mobile) elements. The fundamental informational circuits assuring the survival are the reactive circuit, expressible by attitude, the epigenetic/genetic circuit, absorbing and codifying information to be transmitted to the next generations, and the metabolic circuit, connected to matter (matter pole). The presented analysis allows to extend the informational modeling of consciousness to an Informational Model of Consciousness and Organism, fully describing the composition/functions of the organism in terms of information/matter and neurosciences concept. (shrink)

New York City has extensive public health regulations. Some regulations aim to reduce smoking, and they include high cigarette taxes and bans on smoking in public places such as bars, restaurants, public beaches, and public parks. Other regulations aim to combat obesity. They include regulations requiring display of calorie information on some restaurant menus and the elimination of transfats in much public cooking. One important issue is whether New York City officials -- including both public health officials and other city (...) officials -- have adequately explained the justification to the public. Explanation has practical importance; the public might not back controversial and restrictive regulations unless offered a good rationale. But explanation is also an official duty, since public officials should make their reasoning transparent to their constituents. This article argues that New York City has not adequately communicated the rationales for its regulations to the public. It then offers several suggestions for improving public communication. After laying out those suggestions, this article points out that even if communication were improved, New York City’s regulations would still raise difficult philosophical issues. Those issues are briefly discussed in the final sections. NOTE: this is a reprint of a conference presentation. (shrink)

In India most of the diseases caused by food borne illness, resulting in more number of hospitalizations and deaths are happened. For the reason we are designing a project called food detection system using Internet Of Things (IOT). It is used to test a freshness food like meat, fruits. Different sensor are used to testing a food quality like, pH sensor is used to test a salt content of the food and normal pH value is stored in IOT server and (...) compared to that food. The colour food is checked or abnormal condition. The fruit freshness is tested using image processing testing colour of food and testing food freshness. In this way we are checking food quality in an effective way to avoid food borne illness and buy a healthy food and make a human wealthy. (shrink)

Agriculture is critical to the growth of an agricultural country. Many industries, including agricultural, have been altered as a result of the fast rise of Internet of Things-based technology. In India, farming employs over 70% of the people and generates one-third of the nation's capital. Agriculture-related issues have traditionally hampered the country's progress. The only answer to this challenge is smart agriculture, which involves upgrading conventional agricultural processes. Solutions based on IoT are being developed to autonomously manage and monitor agricultural (...) crops with minimum human intervention. Many elements of technology engaged in the realm of IoT in agriculture are covered in this article. It describes the essential components of IoT-based smart farming. Farmers benefit from IoTbased Agriculture by collecting live knowledge (Temperature, Soil Moisture, and Humidity) of agricultural data. These real-time measurements enable farmers to experiment with new agricultural techniques in order to boost average crop yields as well as plant quality. All of these actions will be controlled by any remote smart device or computer linked to the Internet, and they will be carried out by connecting sensors, Wi-Fi or ZigBee modules, cameras, and actuators with a Raspberry Pi and a microcontroller. (shrink)

Internet of Things (IoT) conceptualizes the idea of remotely connecting and monitoring real world objects (things) through the Internet [1]. When it comes to our house, this concept can be aptly incorporated to make it smarter, safer and automated. This IoT project focuses on building a smart wireless home security system which sends alerts to the owner by using Internet in case of any trespass and raises an alarm optionally. Besides, the same can also be utilized for home automation by (...) making use of the same set of sensors. The leverage obtained by preferring this system over the similar kinds of existing systems is that the alerts and the status sent by the Wi-Fi connected microcontroller managed system can be received by the user on his phone from any distance irrespective of whether his mobile phone is connected to the internet. The microcontrolleri used in the current prototype is the TI-CC3200 Launchpad board which comes with an embedded micro-controller and an onboard Wi- Fi shield making use of which all the electrical appliances inside the home can be controlled and managed. (shrink)

One method for preventing the spread of the coronavirus and other contagious diseases is through social distancing. Therefore, creating a tool to measure and quickly discover the precise distance is necessary. In order to prevent physical contact between individuals, this study aimed to detects individuals’ physical distance, through an inaugurated battery-powered device that monitors physical distance through wireless technology. Specifically, in public or crowded areas, to lessen the spread of the virus. This study focuses on detecting people’s physical distance in (...) the region of interest utilizing an Ultrasonic and VL53L0X sensors and determining the significant difference between the two sensors in monitoring physical distance. This study employs an applied experimental research design. The efficiency of both sensors in measuring physical distance was evaluated through analysis. The Ultrasonic and VL53L0X sensors underwent 15 tests. Furthermore, the researchers effectuated a t-test to determine the significant difference between the two sensors. Data gathered revealed that the sensors’ combined mean in terms of measuring physical distance indicates that the ultrasonic sensor performed better than VL53L0X, measuring 134.7 cm, notwithstanding 99.8 cm for the VL53L0X sensor. Complementary to this, the results of the t-test show that the VL53L0X sensor and Ultrasonic sensor have a significant difference in terms of distance precision. (shrink)

t. This paper presents a sensor-based approach to developing a gesture-controlled robotic vehicle, designed to enhance human-machine interaction in a more intuitive and accessible manner. The system translates hand movements, detected through accelerometers and gyroscopes within a wearable device, into commands that control the vehicle. Traditional methods for operating robotic systems, such as joysticks or remote controls, often require physical interaction, limiting their effectiveness, especially for individuals with disabilities or in environments where hands-free control is essential. This approach offers a (...) non-contact, real-time control mechanism, detecting hand gestures without relying on visual cues, thereby reducing computational load and ensuring stable performance even under varying lighting conditions. The implementation involves sensor calibration, data acquisition, and processing via microcontrollers such as Arduino or ESP32, coupled with a motor control system for vehicle operation. Testing results demonstrate the accuracy and low-latency response of the gesture-based control system. The primary objective is to make this technology widely accessible, offering a scalable solution for various applications, including assistive technologies and robotics. Preliminary findings confirm the system’s effectiveness, opening the door for further real-world applications. (shrink)

This paper shows the smart walking stick based on ultrasonic sensors and Arduino for outwardly debilitated individuals. There are roughly 37 million individuals over the globe who are visually impaired as indicated by the World Health Organization. Individuals with visual inabilities are regularly subjected to outer help which can be given by people, trained dogs, or electronic gadgets as supportive networks for basic assistance. Thus, this played as the motivation to develop a smart cane white stick to survive these (...) restrictions which includes ultrasonic sensors at particular positions to the stick that gave data about nature to the client by initiating the signal sound and vibrations. We proposed minimal effort and light weight framework structured with micro controller that processes signal and alerts the visually impaired person over any obstacle, water or dark areas through beeping sounds or vibrations. The system comprises of obstacle and moisture detection sensors for process of receiving, processing and sending signals to the alarm system which finally alerts the user for prompt action. The system was designed, programmed using Java language and tried for exactness by the visually impaired. Our gadget can recognize obstacle inside the separation of around 2m from the client. (shrink)