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)

—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)

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.

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)

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)

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)

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)

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.

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)

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)

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.

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)

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)

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)

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.

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)

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)

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)

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)

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)

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)

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.

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)

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)

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)

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)

Nowadays, remote monitoring systems have developed gradually to respond for particular needs in healthcare sector, which is an essential pillar in the modern concept of smart living, we propose a smart health monitoring system to monitor patient health conditions, as a smart healthcare system based on the widely spread and evolved technologies. Statistics show that severe Falls, hypertensive heart disease and blood pressure are risk factors for high death rate. To decrease it a preventive measure should be applied providing a (...) real-time health monitoring system, to save patients life at acceptable time. The objectives of this project are to provide an effective system model that will track, trace, and monitor patient’s movement, location, vital readings like heartbeat pulses, body temperature in order to provide efficient medical services in time. In proposed system data will be captured using sensors and compared with a predefined threshold. After processing it will send the Message for support to Relatives/Caretakers which will contain the Location, Heartbeat Values and Body temperature. (shrink)

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. This paper presents an optimized approach to aggregated packet transmission in duty-cycled WSNs, utilizing (...) advanced optimization techniques to enhance energy efficiency, reduce latency, and improve network throughput. By aggregating data packets from multiple nodes before transmission, the proposed method minimizes the number of transmissions, thereby conserving energy. 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. T. (shrink)

This work has been designed to develop an a dynamic road signal based on an emergency with density. The sync signal automatically switches to detecting traffic density at the intersection. Traffic congestion is a serious problem in many large cities around the world and has become a nightmare for travelers in these cities. The conventional traffic light system is based on the concept of fixed time assigned to each side of the join that cannot be varied by varying traffic density. (...) The tie times assigned are fixed. But in an emergency, emergency timings change according to the distance and depth of the traffic. At the time the emergency vehicle is read by the receiver it will execute the management of the traffic light. These projects are infrared proximity sensors in the sightline configuration through the load to detect the traffic light density. The vehicle density is measured in several sectors based on the times assigned as a result. Every crossing of the emergency vehicle logs the data's to the cloud. This log signal would help with the destination acknowledgment. This synchronization will greatly reduce traffic jam. -/- . (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)

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, 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)

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)

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)

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)

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)

Cameras, microphones, and other sensors continue to proliferate in the world around us. I offer a new metaphor for conceptualizing these technologies: they are _digital wormholes_, transmitting representations of human persons between disparate points in space–time. We frequently cannot tell when they are operational, what kinds of data they are collecting, where the data may reappear in the future, and how the data can be used against us. The wormhole metaphor makes the mysteriousness of digital sensors salient: digital sensors have (...) brought us to a strange place. If humans are to be capable of making sensible decisions while under observation by digital sensors, we must improve the epistemic position of potential sensor subjects. (shrink)

The proposed sensor device for dragline operator is designed to enhance environmental safety by detecting and alerting operators to climate change impacts and potential hazards. Utilizing advanced sensor technology, this device continuously monitors weather conditions, such as heavy rain, strong winds, and extreme temperatures. When a hazard is detected, the device provides real-time alerts through an intuitive interface, enabling operators to take immediate action to mitigate risks. This proactive approach ensures operators are well-informed about their surroundings, significantly reducing (...) the risk of accidents and promoting a safer working environment. Additionally, the sensor device seamlessly integrates with existing dragline systems, ensuring compatibility and ease of adoption. By enhancing situational awareness and facilitating timely responses to environmental threats, this sensor device represents a critical advancement in the safety and efficiency of dragline operations in the mining and construction indus. (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)

In recent years, exposome research has been put forward as the next frontier for the study of human health and disease. Exposome research entails the analysis of the totality of environmental exposures and their corresponding biological responses within the human body. Increasingly, this is operationalized by big-data approaches to map the effects of internal as well as external exposures using smart sensors and multiomics technologies. However, the ethical implications of exposome research are still only rarely discussed in the literature. Therefore, (...) we conducted a systematic review of the academic literature regarding both the exposome and underlying research fields and approaches, to map the ethical aspects that are relevant to exposome research. We identify five ethical themes that are prominent in ethics discussions: the goals of exposome research, its standards, its tools, how it relates to study participants, and the consequences of its products. Furthermore, we provide a number of general principles for how future ethics research can best make use of our comprehensive overview of the ethical aspects of exposome research. Lastly, we highlight three aspects of exposome research that are most in need of ethical reflection: the actionability of its findings, the epidemiological or clinical norms applicable to exposome research, and the meaning and action–implications of bias. (shrink)

Analysis of grip force signals tailored to hand and finger movement evolution and changes in grip force control during task execution provide unprecedented functional insight into somatosensory cognition. Somatosensory cognition is a basis of our ability to manipulate, move, and transform objects of the physical world around us, to recognize them on the basis of touch alone, and to grasp them with the right amount of force for lifting and manipulating them. Recent technology has permitted the wireless monitoring of grip (...) force signals recorded from biosensors in the palm of the human hand to track and trace human grip forces deployed in cognitive tasks executed under conditions of variable sensory (visual, auditory) input. Non-invasive multi-finger grip force sensor technology can be exploited to explore functional interactions between somatosensory brain mechanisms and motor control, in particular during learning a cognitive task where the planning and strategic execution of hand movements is essential. Sensorial and cognitive processes underlying manual skills and/or hand-specific (dominant versus non-dominant hand) behaviors can be studied in a variety of contexts by probing selected measurement loci in the fingers and palm of the human hand. Thousands of sensor data recorded from multiple spatial locations can be approached statistically to breathe functional sense into the forces measured under specific task constraints. Grip force patterns in individual performance profiling may reveal the evolution of grip force control as a direct result of cognitive changes during task learning. Grip forces can be functionally mapped to from-global-to-local coding principles in brain networks governing somatosensory processes for motor control in cognitive tasks leading to a specific task expertise or skill. Under the light of a comprehensive overview of recent discoveries into the functional significance of human grip force variations, perspectives for future studies in cognition, in particular the cognitive control of strategic and task relevant hand movements in complex real-world precision task, are pointed out. (shrink)

The chapter deals with the notion of phenomenal realness, which was first systematically explored by Albert Michotte. Phenomenal realness refers to the impression that a perceptual object is perceived to have an autonomous existence in our mind-independent world. Perceptual psychology provides an abundance of phenomena, ranging from amodal completion to picture perception, that indicate that phenomenal realness is an independent perceptual attribute that can be conferred to perceptual objects in different degrees. The chapter outlines a theoretical framework that appears particularly (...) well-suited for dealing with corresponding phenomena. According to this framework, perception can be understood as a triggering of conceptual forms by sensor inputs. It is argued that the attribute of phenomenal realness is based on specific types of internal evaluation functions which deal with the segregation of causes conceived as ‘external’ from those conceived as ‘internal’. These evaluation functions integrate different internal sources of ‘knowledge’ about the potential causes for the activation of conceptual forms and provide markers by which conceptual forms can be tagged as ‘external world objects’. (shrink)

This selective review explores biologically inspired learning as a model for intelligent robot control and sensing technology on the basis of specific examples. Hebbian synaptic learning is discussed as a functionally relevant model for machine learning and intelligence, as explained on the basis of examples from the highly plastic biological neural networks of invertebrates and vertebrates. Its potential for adaptive learning and control without supervision, the generation of functional complexity, and control architectures based on self-organization is brought forward. Learning without (...) prior knowledge based on excitatory and inhibitory neural mechanisms accounts for the process through which survival-relevant or task-relevant representations are either reinforced or suppressed. The basic mechanisms of unsupervised biological learning drive synaptic plasticity and adaptation for behavioral success in living brains with different levels of complexity. The insights collected here point toward the Hebbian model as a choice solution for “intelligent” robotics and sensor systems. Keywords: Hebbian learning; synaptic plasticity; neural networks; self-organization; brain; reinforcement; sensory processing; robot control . (shrink)

Abstract: Climate change presents a critical challenge that demands advanced analytical tools to predict and mitigate its impacts. This paper explores the role of artificial intelligence (AI) in enhancing climate modeling, emphasizing how AI-driven methods are revolutionizing our understanding and response to climate change. By integrating machine learning algorithms with diverse data sources such as satellite imagery, historical climate records, and real-time sensor data, AI improves the accuracy, efficiency, and granularity of climate predictions. The paper reviews key AI techniques, (...) including neural networks and ensemble models, and their applications in simulating extreme weather events and forecasting long-term climate trends. Additionally, it examines the impact of AI-enhanced climate models on policy-making and strategic planning. Despite significant advancements, challenges such as data quality, computational demands, and model interpretability remain. This study underscores the potential of AI to transform climate modeling and highlights areas for future research and development to harness these technologies for a sustainable future. (shrink)

The primary objective of this research is to enhance the precision and speed of stock handling while minimizing human intervention and error. Our design incorporates state-of-the-art sensors, real-time tracking systems, and autonomous robots programmed with advanced algorithms for object identification, gripping, and movement. We propose a systematic workflow for automating the storage and retrieval process, starting from the identification of the stock to its precise placement and retrieval within the storage facility. The design also addresses potential challenges such as robot (...) mobility, collision avoidance, and space optimization. Performance metrics, including accuracy, time efficiency, and system scalability, are measured using simulation-based experiments in a controlled environment. The results show significant improvements in operational efficiency compared to traditional stock management approaches. This integration paves the way for future advancements in fully automated warehouses, reducing the need for human labor and increasing reliability. Finally, we discuss potential enhancements, including AI-based decision-making algorithms, multi-robot collaboration, and integration with Internet of Things (IoT) for real-time data analysis and continuous system improvement. (shrink)

Knill, Kersten, & Mamassian (Chapter 6) provide an interesting discussion of how the Bayesian formulation can be used to help investigate human vision. In their view, computational theories can be based on an ideal observer that uses Bayesian inference to make optimal use of available information. Four factors are important here: the image information used, the output structures estimated, the priors assumed (i.e., knowledge about the structure of the world), and the likelihood function used (i.e., knowledge about the projection of (...) the world onto the sensors). Knill & Kersten argue that such a framework not only helps analyze a perceptual task, but can also help investigators to define it. Two examples are provided (the interpretation of surface contour and the perception of moving shadows) to show how this approach can be used in practice. As the authors admit, most (if not all) perceptual processes are ill-suited to a "strong" Bayesian approach based on a single consistent model of the world. Instead, they argue for a "weak" variant that assumes Bayesian inference to be carried out in modules of more limited scope. But how weak is "weak"? Are such approaches suitable for only a few relatively low-level tasks, or can they be applied more generally? Could a weak Bayesian approach, for example, explain how we would recognize the return of Elvis Presley? The formal modelling of human perception To help get a fix on things, it is useful to examine the fate of an earlier attempt to formalize human perception: the application of information theory. It was once hoped that this theory—a close cousin of the Bayesian formulation—would provide a way to uncover information-handling laws that were largely independent of physical implementation. In this approach, the human nervous system was assumed to have.. (shrink)

Deep learning algorithms are rapidly changing the way in which audiovisual media can be produced. Synthetic audiovisual media generated with deep learning—often subsumed colloquially under the label “deepfakes”—have a number of impressive characteristics; they are increasingly trivial to produce, and can be indistinguishable from real sounds and images recorded with a sensor. Much attention has been dedicated to ethical concerns raised by this technological development. Here, I focus instead on a set of issues related to the notion of synthetic (...) audiovisual media, its place within a broader taxonomy of audiovisual media, and how deep learning techniques differ from more traditional approaches to media synthesis. After reviewing important etiological features of deep learning pipelines for media manipulation and generation, I argue that “deepfakes” and related synthetic media produced with such pipelines do not merely offer incremental improvements over previous methods, but challenge traditional taxonomical distinctions, and pave the way for genuinely novel kinds of audiovisual media. (shrink)

Cognitive organisms have three rather different techniques for intelligently regulating their intake of environmental information. In order of the time needed to uncover information they are: 1. control of attention: within an image produced by a given sensor certain elements can be selected for additional processing; 2. control of gaze: the orientation and resolution (center of foveation) of the sensor can be regulated to create a new image; 3. control of activity: certain non-perceptual actions can be performed to (...) increase the probability of unearthing salient information that currently is unavailable, hard to detect, or hard to compute. (shrink)