Search results for: biomedical sensors
890 Predictive Maintenance of Electrical Induction Motors Using Machine Learning
Authors: Muhammad Bilal, Adil Ahmed
Abstract:
This study proposes an approach for electrical induction motor predictive maintenance utilizing machine learning algorithms. On the basis of a study of temperature data obtained from sensors put on the motor, the goal is to predict motor failures. The proposed models are trained to identify whether a motor is defective or not by utilizing machine learning algorithms like Support Vector Machines (SVM) and K-Nearest Neighbors (KNN). According to a thorough study of the literature, earlier research has used motor current signature analysis (MCSA) and vibration data to forecast motor failures. The temperature signal methodology, which has clear advantages over the conventional MCSA and vibration analysis methods in terms of cost-effectiveness, is the main subject of this research. The acquired results emphasize the applicability and effectiveness of the temperature-based predictive maintenance strategy by demonstrating the successful categorization of defective motors using the suggested machine learning models.Keywords: predictive maintenance, electrical induction motors, machine learning, temperature signal methodology, motor failures
Procedia PDF Downloads 104889 Assessment of Frying Material by Deep-Fat Frying Method
Authors: Brinda Sharma, Saakshi S. Sarpotdar
Abstract:
Deep-fat frying is popular standard method that has been studied basically to clarify the complicated mechanisms of fat decomposition at high temperatures and to assess their effects on human health. The aim of this paper is to point out the application of method engineering that has been recently improved our understanding of the fundamental principles and mechanisms concerned at different scales and different times throughout the process: pretreatment, frying, and cooling. It covers the several aspects of deep-fat drying. New results regarding the understanding of the frying method that are obtained as a results of major breakthroughs in on-line instrumentation (heat, steam flux, and native pressure sensors), within the methodology of microstructural and imaging analysis (NMR, MRI, SEM) and in software system tools for the simulation of coupled transfer and transport phenomena. Such advances have opened the approach for the creation of significant information of the behavior of varied materials and to the event of latest tools to manage frying operations via final product quality in real conditions. Lastly, this paper promotes an integrated approach to the frying method as well as numerous competencies like those of chemists, engineers, toxicologists, nutritionists, and materials scientists also as of the occupation and industrial sectors.Keywords: frying, cooling, imaging analysis (NMR, MRI, SEM), deep-fat frying
Procedia PDF Downloads 423888 Investigating the Vehicle-Bicyclists Conflicts using LIDAR Sensor Technology at Signalized Intersections
Authors: Alireza Ansariyar, Mansoureh Jeihani
Abstract:
Light Detection and Ranging (LiDAR) sensors are capable of recording traffic data including the number of passing vehicles and bicyclists, the speed of vehicles and bicyclists, and the number of conflicts among both road users. In order to collect real-time traffic data and investigate the safety of different road users, a LiDAR sensor was installed at Cold Spring Ln – Hillen Rd intersection in Baltimore City. The frequency and severity of collected real-time conflicts were analyzed and the results highlighted that 122 conflicts were recorded over a 10-month time interval from May 2022 to February 2023. By using an innovative image-processing algorithm, a new safety Measure of Effectiveness (MOE) was proposed to recognize the critical zones for bicyclists entering each zone. Considering the trajectory of conflicts, the results of the analysis demonstrated that conflicts in the northern approach (zone N) are more frequent and severe. Additionally, sunny weather is more likely to cause severe vehicle-bike conflicts.Keywords: LiDAR sensor, post encroachment time threshold (PET), vehicle-bike conflicts, a measure of effectiveness (MOE), weather condition
Procedia PDF Downloads 216887 Wireless Capsule Endoscope - Antenna and Channel Characterization
Authors: Mona Elhelbawy, Mac Gray
Abstract:
Traditional wired endoscopy is an intrusive process that requires a long flexible tube to be inserted through the patient’s mouth while intravenously sedated. Only images of the upper 4 feet of stomach, colon, and rectum can be captured, leaving the remaining 20 feet of small intestines. Wireless capsule endoscopy offers a painless, non-intrusive, efficient and effective alternative to traditional endoscopy. In wireless capsule endoscopy (WCE), ingestible vitamin-pill-shaped capsules with imaging capabilities, sensors, batteries, and antennas are designed to send images of the gastrointestinal (GI) tract in real time. In this paper, we investigate the radiation performance and specific absorption rate (SAR) of a miniature conformal capsule antenna operating at the Medical Implant Communication Service (MICS) frequency band in the human body. We perform numerical simulations using the finite element method based commercial software, high-frequency structure simulator (HFSS) and the ANSYS human body model (HBM). We also investigate the in-body channel characteristics between the implantable capsule and an external antenna placed on the surface of the human body.Keywords: IEEE 802.15.6, MICS, SAR, WCE
Procedia PDF Downloads 121886 Structural Health Monitoring of Buildings and Infrastructure
Authors: Mojtaba Valinejadshoubi, Ashutosh Bagchi, Osama Moselhi
Abstract:
Structures such as buildings, bridges, dams, wind turbines etc. need to be maintained against various factors such as deterioration, excessive loads, environment, temperature, etc. Choosing an appropriate monitoring system is important for determining any critical damage to a structure and address that to avoid any adverse consequence. Structural Health Monitoring (SHM) has emerged as an effective technique to monitor the health of the structures. SHM refers to an ongoing structural performance assessment using different kinds of sensors attached to or embedded in the structures to evaluate their integrity and safety to help engineers decide on rehabilitation measures. Ability of SHM in identifying the location and severity of structural damages by considering any changes in characteristics of the structures such as their frequency, stiffness and mode shapes helps engineers to monitor the structures and take the most effective corrective actions to maintain their safety and extend their service life. The main objective of this study is to review the overall SHM process specifically determining the natural frequency of an instrumented simply-supported concrete beam using modal testing and finite element model updating.Keywords: structural health monitoring, natural frequency, modal analysis, finite element model updating
Procedia PDF Downloads 330885 Synthesis and Optimization of Bio Metal-Organic Framework with Permanent Porosity
Authors: Tia Kristian Tajnšek, Matjaž Mazaj, Nataša Zabukovec Logar
Abstract:
Metal-organic frameworks (MOFs) with their specific properties and the possibility of tuning the structure represent excellent candidates for use in the biomedical field. Their advantage lies in large pore surfaces and volumes, as well as the possibility of using bio-friendly or bioactive constituents. So-called bioMOFs are representatives of MOFs, which are constructed from at least one biomolecule (metal, a small bioactive molecule in metal clusters and/or linker) and are intended for bio-application (usually in the field of medicine; most commonly drug delivery). When designing a bioMOF for biomedical applications, we should adhere to some guidelines for an improved toxicological profile of the material. Such as (i) choosing an endogenous/nontoxic metal, (ii) GRAS (generally recognized as safe) linker, and (iii) nontoxic solvents. Design and synthesis of bioNICS-1 (bioMOF of National Institute of Chemistry Slovenia – 1) consider all these guidelines. Zinc (Zn) was chosen as an endogenous metal with an agreeable recommended daily intake (RDI) and LD50 value, and ascorbic acid (Vitamin C) was chosen as a GRAS and active linker. With these building blocks, we have synthesized a bioNICS-1 material. The synthesis was done in ethanol using a solvothermal method. The synthesis protocol was further optimized in three separate ways. Optimization of (i) synthesis parameters to improve the yield of the synthesis, (ii) input reactant ratio and addition of specific modulators for production of larger crystals, and (iii) differing of the heating source (conventional, microwave and ultrasound) to produce nano-crystals. With optimization strategies, the synthesis yield was increased. Larger crystals were prepared for structural analysis with the use of a proper species and amount of modulator. Synthesis protocol was adjusted to different heating sources, resulting in the production of nano-crystals of bioNICS-1 material. BioNICS-1 was further activated in ethanol and structurally characterized, resolving the crystal structure of new material.Keywords: ascorbic acid, bioMOF, MOF, optimization, synthesis, zinc ascorbate
Procedia PDF Downloads 131884 Verification of Space System Dynamics Using the MATLAB Identification Toolbox in Space Qualification Test
Authors: Yuri V. Kim
Abstract:
This article presents a new approach to the Functional Testing of Space Systems (SS). It can be considered as a generic test and used for a wide class of SS that from the point of view of System Dynamics and Control may be described by the ordinary differential equations. Suggested methodology is based on using semi-natural experiment- laboratory stand that doesn’t require complicated, precise and expensive technological control-verification equipment. However, it allows for testing system as a whole totally assembled unit during Assembling, Integration and Testing (AIT) activities, involving system hardware (HW) and software (SW). The test physically activates system input (sensors) and output (actuators) and requires recording their outputs in real time. The data is then inserted in laboratory PC where it is post-experiment processed by Matlab/Simulink Identification Toolbox. It allows for estimating system dynamics in form of estimation of system differential equations by the experimental way and comparing them with expected mathematical model prematurely verified by mathematical simulation during the design process.Keywords: system dynamics, space system ground tests and space qualification, system dynamics identification, satellite attitude control, assembling, integration and testing
Procedia PDF Downloads 154883 Electronic Nose Based on Metal Oxide Semiconductor Sensors as an Alternative Technique for the Spoilage Classification of Oat Milk
Authors: A. Deswal, N. S. Deora, H. N. Mishra
Abstract:
The aim of the present study was to develop a rapid method for electronic nose for online quality control of oat milk. Analysis by electronic nose and bacteriological measurements were performed to analyse spoilage kinetics of oat milk samples stored at room temperature and refrigerated conditions for up to 15 days. Principal component analysis (PCA), discriminant factorial analysis (DFA) and soft independent modelling by class analogy (SIMCA) classification techniques were used to differentiate the samples of oat milk at different days. The total plate count (bacteriological method) was selected as the reference method to consistently train the electronic nose system. The e-nose was able to differentiate between the oat milk samples of varying microbial load. The results obtained by the bacteria total viable counts showed that the shelf-life of oat milk stored at room temperature and refrigerated conditions were 20 hours and 13 days, respectively. The models built classified oat milk samples based on the total microbial population into “unspoiled” and “spoiled”.Keywords: electronic-nose, bacteriological, shelf-life, classification
Procedia PDF Downloads 251882 Implementation of ISO 26262: Issues and Challenges
Authors: Won Jung, Azianti Ismail
Abstract:
Functional safety is about electrical, electronics, and programmable electronic safety-related system focuses on the potential risk of malfunction which may have a significant impact on the safety of humans and/or the environment based on IEC 61508. In November 2011, the automotive industry has been introduced to automotive functional safety ISO 26262 which addresses the complete safety installation from sensor to actuator with its technical as well as management issues. Nowadays, most of the modern automobiles are equipped with embedded electronic systems which include many Electronic Controller Units (ECUs), electronic sensors, signals, bus systems and coding. Due to upcoming more sophisticated systems installed in automobiles, the need to carry out detailed safety is very crucial. Assimilation of existing practices with this new standard is a major challenge for the automotive industry in reducing redundancy, time and resources. Therefore, this paper will analyze the research trends on pre and post introduction of ISO 26262 through publications as well as to take a glimpse in the activities for implementing this standard by the automotive manufacturers around the world. It is going to highlight issues and challenges which have been discussed among the experts in this field. Even though it will take some time for this standard to be fully implemented, the benefits from this implementation will raise the competitiveness in the global automotive market.Keywords: ISO 26262, automotive, functional safety, implementation, standard, challenges
Procedia PDF Downloads 387881 A Study on Using Network Coding for Packet Transmissions in Wireless Sensor Networks
Authors: Rei-Heng Cheng, Wen-Pinn Fang
Abstract:
A wireless sensor network (WSN) is composed by a large number of sensors and one or a few base stations, where the sensor is responsible for detecting specific event information, which is sent back to the base station(s). However, how to save electricity consumption to extend the network lifetime is a problem that cannot be ignored in the wireless sensor networks. Since the sensor network is used to monitor a region or specific events, how the information can be reliably sent back to the base station is surly important. Network coding technique is often used to enhance the reliability of the network transmission. When a node needs to send out M data packets, it encodes these data with redundant data and sends out totally M + R packets. If the receiver can get any M packets out from these M + R packets, it can decode and get the original M data packets. To transmit redundant packets will certainly result in the excess energy consumption. This paper will explore relationship between the quality of wireless transmission and the number of redundant packets. Hopefully, each sensor can overhear the nearby transmissions, learn the wireless transmission quality around it, and dynamically determine the number of redundant packets used in network coding.Keywords: energy consumption, network coding, transmission reliability, wireless sensor networks
Procedia PDF Downloads 384880 Long Short-Term Memory Based Model for Modeling Nicotine Consumption Using an Electronic Cigarette and Internet of Things Devices
Authors: Hamdi Amroun, Yacine Benziani, Mehdi Ammi
Abstract:
In this paper, we want to determine whether the accurate prediction of nicotine concentration can be obtained by using a network of smart objects and an e-cigarette. The approach consists of, first, the recognition of factors influencing smoking cessation such as physical activity recognition and participant’s behaviors (using both smartphone and smartwatch), then the prediction of the configuration of the e-cigarette (in terms of nicotine concentration, power, and resistance of e-cigarette). The study uses a network of commonly connected objects; a smartwatch, a smartphone, and an e-cigarette transported by the participants during an uncontrolled experiment. The data obtained from sensors carried in the three devices were trained by a Long short-term memory algorithm (LSTM). Results show that our LSTM-based model allows predicting the configuration of the e-cigarette in terms of nicotine concentration, power, and resistance with a root mean square error percentage of 12.9%, 9.15%, and 11.84%, respectively. This study can help to better control consumption of nicotine and offer an intelligent configuration of the e-cigarette to users.Keywords: Iot, activity recognition, automatic classification, unconstrained environment
Procedia PDF Downloads 213879 Intelligent Tooling Embedded Sensors for Monitoring the Wear of Cutting Tools in Turning Applications
Authors: Hatim Laalej, Jon Stammers
Abstract:
In machining, monitoring of tool wear is essential for achieving the desired dimensional accuracy and surface finish of a machined workpiece. Currently, the task of monitoring the wear on the cutting tool is carried out by the operator who performs manual inspections of the cutting tool, causing undesirable stoppages of machine tools and consequently resulting in costs incurred from loss of productivity. The cutting tool consumable costs may also be higher than necessary when tools are changed before the end of their useful life. Furthermore, damage can be caused to the workpiece when tools are not changed soon enough leading to a significant increase in the costs of manufacturing. The present study is concerned with the development of break sensor printed on the flank surface of poly-crystalline diamond (PCD) cutting to perform on-line condition monitoring of the cutting tool used to machine Titanium Ti-6al-4v bar. The results clearly show that there is a strong correlation between the break sensor measurements and the amount of wear in the cutting tool. These findings are significant in that they help the user/operator of the machine tool to determine the condition of the cutting tool without the need of performing manual inspection, thereby reducing the manufacturing costs such as the machine down time.Keywords: machining, manufacturing, tool wear, signal processing
Procedia PDF Downloads 233878 The Use of Remote Sensing in the Study of Vegetation Jebel Boutaleb, Setif, Algeria
Authors: Khaled Missaoui, Amina Beldjazia, Rachid Gharzouli, Yamna Djellouli
Abstract:
Optical remote sensing makes use of visible, near infrared and short-wave infrared sensors to form images of the earth's surface by detecting the solar radiation reflected from targets on the ground. Different materials reflect and absorb differently at different wavelengths. Thus, the targets can be differentiated by their spectral reflectance signatures in the remotely sensed images. In this work, we are interested to study the distribution of vegetation in the massif forest of Boutaleb (North East of Algeria) which suffered between 1998 and 1999 very large fires. In this case, we use remote sensing with Landsat images from two dates (1984 and 2000) to see the results of these fires. Vegetation has a unique spectral signature which enables it to be distinguished readily from other types of land cover in an optical/near-infrared image. Normalized Difference Vegetation Index (NDVI) is calculated with ENVI 4.7 from Band 3 and 4. The results showed a very important floristic diversity in this forest. The comparison of NDVI from the two dates confirms that there is a decrease of the density of vegetation in this area due to repeated fires.Keywords: remote sensing, boutaleb, diversity, forest
Procedia PDF Downloads 548877 An Internet of Things-Based Weight Monitoring System for Honey
Authors: Zheng-Yan Ruan, Chien-Hao Wang, Hong-Jen Lin, Chien-Peng Huang, Ying-Hao Chen, En-Cheng Yang, Chwan-Lu Tseng, Joe-Air Jiang
Abstract:
Bees play a vital role in pollination. This paper focuses on the weighing process of honey. Honey is usually stored at the comb in a hive. Bee farmers brush bees away from the comb and then collect honey, and the collected honey is weighed afterward. However, such a process brings strong negative influences on bees and even leads to the death of bees. This paper therefore presents an Internet of Things-based weight monitoring system which uses weight sensors to measure the weight of honey and simplifies the whole weighing procedure. To verify the system, the weight measured by the system is compared to the weight of standard weights used for calibration by employing a linear regression model. The R2 of the regression model is 0.9788, which suggests that the weighing system is highly reliable and is able to be applied to obtain actual weight of honey. In the future, the weight data of honey can be used to find the relationship between honey production and different ecological parameters, such as bees’ foraging behavior and weather conditions. It is expected that the findings can serve as critical information for honey production improvement.Keywords: internet of things, weight, honey, bee
Procedia PDF Downloads 451876 Topographic Mapping of Farmland by Integration of Multiple Sensors on Board Low-Altitude Unmanned Aerial System
Authors: Mengmeng Du, Noboru Noguchi, Hiroshi Okamoto, Noriko Kobayashi
Abstract:
This paper introduced a topographic mapping system with time-saving and simplicity advantages based on integration of Light Detection and Ranging (LiDAR) data and Post Processing Kinematic Global Positioning System (PPK GPS) data. This topographic mapping system used a low-altitude Unmanned Aerial Vehicle (UAV) as a platform to conduct land survey in a low-cost, efficient, and totally autonomous manner. An experiment in a small-scale sugarcane farmland was conducted in Queensland, Australia. Subsequently, we synchronized LiDAR distance measurements that were corrected by using attitude information from gyroscope with PPK GPS coordinates for generation of precision topographic maps, which could be further utilized for such applications like precise land leveling and drainage management. The results indicated that LiDAR distance measurements and PPK GPS altitude reached good accuracy of less than 0.015 m.Keywords: land survey, light detection and ranging, post processing kinematic global positioning system, precision agriculture, topographic map, unmanned aerial vehicle
Procedia PDF Downloads 225875 Small Fixed-Wing UAV Physical Based Modeling, Simulation, and Validation
Authors: Ebrahim H. Kapeel, Ehab Safwat, Hossam Hendy, Ahmed M. Kamel, Yehia Z. Elhalwagy
Abstract:
Motivated by the problem of the availability of high-fidelity flight simulation models for small unmanned aerial vehicles (UAVs). This paper focuses on the geometric-mass inertia modeling and the actuation system modeling for the small fixed-wing UAVs. The UAV geometric parameters for the body, wing, horizontal and vertical tail are physically measured. Pendulum experiment with high-grade sensors and data analysis using MATLAB is used to estimate the airplane moment of inertia (MOI) model. Finally, UAV’s actuation system is modeled by estimating each servo transfer function by using the system identification, which uses experimental measurement for input and output angles through using field-programmable gate array (FPGA). Experimental results for the designed models are given to illustrate the effectiveness of the methodology. It also gives a very promising result to finalize the open-loop flight simulation model through modeling the propulsion system and the aerodynamic system.Keywords: unmanned aerial vehicle, geometric-mass inertia model, system identification, Simulink
Procedia PDF Downloads 170874 IoT Continuous Monitoring Biochemical Oxygen Demand Wastewater Effluent Quality: Machine Learning Algorithms
Authors: Sergio Celaschi, Henrique Canavarro de Alencar, Claaudecir Biazoli
Abstract:
Effluent quality is of the highest priority for compliance with the permit limits of environmental protection agencies and ensures the protection of their local water system. Of the pollutants monitored, the biochemical oxygen demand (BOD) posed one of the greatest challenges. This work presents a solution for wastewater treatment plants - WWTP’s ability to react to different situations and meet treatment goals. Delayed BOD5 results from the lab take 7 to 8 analysis days, hindered the WWTP’s ability to react to different situations and meet treatment goals. Reducing BOD turnaround time from days to hours is our quest. Such a solution is based on a system of two BOD bioreactors associated with Digital Twin (DT) and Machine Learning (ML) methodologies via an Internet of Things (IoT) platform to monitor and control a WWTP to support decision making. DT is a virtual and dynamic replica of a production process. DT requires the ability to collect and store real-time sensor data related to the operating environment. Furthermore, it integrates and organizes the data on a digital platform and applies analytical models allowing a deeper understanding of the real process to catch sooner anomalies. In our system of continuous time monitoring of the BOD suppressed by the effluent treatment process, the DT algorithm for analyzing the data uses ML on a chemical kinetic parameterized model. The continuous BOD monitoring system, capable of providing results in a fraction of the time required by BOD5 analysis, is composed of two thermally isolated batch bioreactors. Each bioreactor contains input/output access to wastewater sample (influent and effluent), hydraulic conduction tubes, pumps, and valves for batch sample and dilution water, air supply for dissolved oxygen (DO) saturation, cooler/heater for sample thermal stability, optical ODO sensor based on fluorescence quenching, pH, ORP, temperature, and atmospheric pressure sensors, local PLC/CPU for TCP/IP data transmission interface. The dynamic BOD system monitoring range covers 2 mg/L < BOD < 2,000 mg/L. In addition to the BOD monitoring system, there are many other operational WWTP sensors. The CPU data is transmitted/received to/from the digital platform, which in turn performs analyses at periodic intervals, aiming to feed the learning process. BOD bulletins and their credibility intervals are made available in 12-hour intervals to web users. The chemical kinetics ML algorithm is composed of a coupled system of four first-order ordinary differential equations for the molar masses of DO, organic material present in the sample, biomass, and products (CO₂ and H₂O) of the reaction. This system is solved numerically linked to its initial conditions: DO (saturated) and initial products of the kinetic oxidation process; CO₂ = H₂0 = 0. The initial values for organic matter and biomass are estimated by the method of minimization of the mean square deviations. A real case of continuous monitoring of BOD wastewater effluent quality is being conducted by deploying an IoT application on a large wastewater purification system located in S. Paulo, Brazil.Keywords: effluent treatment, biochemical oxygen demand, continuous monitoring, IoT, machine learning
Procedia PDF Downloads 68873 The Application of Distributed Optical Strain Sensing to Measure Rock Bolt Deformation Subject to Bedding Shear
Authors: Thomas P. Roper, Brad Forbes, Jurij Karlovšek
Abstract:
Shear displacement along bedding defects is a well-recognised behaviour when tunnelling and mining in stratified rock. This deformation can affect the durability and integrity of installed rock bolts. In-situ monitoring of rock bolt deformation under bedding shear cannot be accurately derived from traditional strain gauge bolts as sensors are too large and spaced too far apart to accurately assess concentrated displacement along discrete defects. A possible solution to this is the use of fiber optic technologies developed for precision monitoring. Distributed Optic Sensor (DOS) embedded rock bolts were installed in a tunnel project with the aim of measuring the bolt deformation profile under significant shear displacements. This technology successfully measured the 3D strain distribution along the bolts when subjected to bedding shear and resolved the axial and lateral strain constituents in order to determine the deformational geometry of the bolts. The results are compared well with the current visual method for monitoring shear displacement using borescope holes, considering this method as suitable.Keywords: distributed optical strain sensing, rock bolt, bedding shear, sandstone tunnel
Procedia PDF Downloads 156872 Solid-State Luminescence of Fluorenone Grafted onto Cellulose Aldehyde Backbone Using Different Organic Amine Spacers
Authors: Isam M. Arafa, Mazin Y. Shatnawi, Yaser A. Yousef, Batool Zaid Al-Momani
Abstract:
The present work describes the preparation, characterization, and luminescence of a series of fluorenone (FL) based luminophores grafted onto modified cellulose microfibers. The FL is condensed onto cellulose aldehyde using three diamine spacers (H₂N-NH₂, H₂N(CH₂)₂NH₂ and H₂N(CH₂)₃NH₂) to afford Cell=Spacer=FL. The obtained products were characterized by spectroscopic (FT-IR, UV–Vis), thermal gravimetric analysis (TGA), and microscopic (Optical, SEM) techniques. The UV-Vis spectra of the FL=N(CH₂)ₓNH₂ (x = 0, 2, 3) moieties show that they are transparent in the 375- 800 nm region while they exhibit intense absorption band below 350 nm attributed to n-π* and π-π* transitions. The solid-state photoluminescence (PLs-s) of the cold-pressed pellets of the FL=N(CH₂)ₓNH₂ and Cell=Spacer=FL placed in a quartz cuvette show strong emission in the 500-550 nm region upon irradiation with Xe lamp light (λex = 320 nm). The PLs-s green emission of the grafted Cell=Spacer=FL was evaluated relative to that of the FL-based precursor. These grafted conjugated products have the potential to be used as analyte sensors for typical nitroaromatics/aromatic amines and be further extended to immunoassay studies for aromatic amino acids such as phenylalanine and histidine.Keywords: luminescence, cellulose, fluorenone, grafting, solid state
Procedia PDF Downloads 62871 Smart Trash Can Interface between Origin and Destination Waste Management
Authors: Fatemeh Ghorbani
Abstract:
The increase in population in the cities has also led to the increase and accumulation of urban waste. Managing and organizing waste is an action that must be taken to prevent environmental pollution. Separation of waste from the source is the first step that must be taken to determine whether the waste should be buried, burned, recycled, or used in the industry according to its type. Separation of trash is a cultural work that the general public must learn the necessity of doing; then, it is necessary to provide suitable conditions for collecting this waste. It is necessary to put segregated garbage cans in the city so that people can put the garbage in the right place. In this research, a smart trash can has been designed, which is connected to the central system of the municipality and has information on the units of each neighborhood separately. By entering the postal code on the page connected to each bin and entering the type of waste, the section related to the waste in the existing bin is opened and the person places the waste in the desired section. In addition, all the bins are connected to the municipal system, and the sensors in it warn each relevant body about the fullness and emptiness of the bins. Also, people can know how full and empty the bins around their building are through the designed application connected to the system. In this way, each organization collects its desired waste, wet and dry waste are separated from the beginning, and city pollution and unpleasant odors are also prevented.Keywords: connector, smart trash can, waste management
Procedia PDF Downloads 60870 Analysis of the Accuracy of Earth Movement with Drone Surveys
Authors: Raúl Pereda García, Julio Manuel de Luis Ruiz, Elena Castillo López, Rubén Pérez Álvarez, Felipe Piña García
Abstract:
New technologies for the capture of point clouds have experienced a great advance in recent years. In this way, its use has been extended in geomatics, providing measurement solutions that have been popularized without there being, many times, a detailed study of its accuracy. This research focuses on the study of the viability of topographic works with drones incorporating different sensors sensitive to the visible spectrum. The fundamentals have been applied to a road, located in Cantabria (Spain), where a platform extension and the reform of a riprap were being constructed. A total of six flights were made during two months, all of them with GPS as part of the photogrammetric process, and the results were contrasted with those measured with total station. The obtained results show that the choice of the camera and the planning of the flight have an important impact on the accuracy. In fact, the representations with a level of detail corresponding to 1/1000 scale are admissible, depending on the existing vegetation, and obtaining better results in the area of the riprap. This set of techniques is, therefore, suitable for the control of earthworks in road works but with certain limitations which are exposed in this paper.Keywords: drone, earth movement control, global position system, surveying technology.
Procedia PDF Downloads 175869 Non-Contact Characterization of Standard Liquids Using Waveguide at 12.4 to18 Ghz Frequency Span
Authors: Kasra Khorsand-Kazemi, Bianca Vizcaino, Mandeep Chhajer Jain, Maryam Moradpour
Abstract:
This work presents an approach to characterize a non- contact microwave sensor using waveguides for different standard liquids such as ethanol, methanol and 2-propanol (Isopropyl Alcohol). Wideband waveguides operating between 12.4GHz to 18 GHz form the core of the sensing structure. Waveguides are sensitive to changes in conductivity of the sample under test (SUT), making them an ideal tool to characterize different polar liquids. As conductivity of the sample under test increase, the loss tangent of the material increase, thereby decreasing the S21 (dB) response of the waveguide. Among all the standard liquids measured, methanol exhibits the highest conductivity and 2-Propanol exhibits the lowest. The cutoff frequency measured for ethanol, 2-propanol, and methanol are 10.28 GHz, 10.32 GHz, and 10.38 GHz respectively. The measured results can be correlated with the loss tangent results of the standard liquid measured using the dielectric probe. This conclusively enables us to characterize different liquids using waveguides expanding the potential future applications in domains ranging from water quality management to bio-medical, chemistry and agriculture.Keywords: Waveguides, , Microwave sensors, , Standard liquids characterization, Non-contact sensing
Procedia PDF Downloads 132868 Structural and Electrical Properties of VO₂/ZnO Nanostructures
Authors: Sang-Wook Han, Zhenlan Jin, In-Hui Hwang, Chang-In Park
Abstract:
We examined structural and electrical properties of uniformly-oriented VO₂/ZnO nanostructures. VO₂ was deposited on ZnO templates by using a direct current-sputtering deposition. Scanning electron microscope and transmission electron microscope measurements indicated that b-oriented VO₂ were uniformly crystallized on ZnO templates with different lengths. VO₂/ZnO formed nanorods on ZnO nanorods with length longer than 250 nm. X-ray absorption fine structure at V K edge of VO₂/ZnO showed M1 and R phases of VO₂ at 30 and 100 ℃, respectively, suggesting structural phase transition between temperatures. Temperature-dependent resistance measurements of VO₂/ZnO nanostructures revealed metal-to-insulator transition at 65 ℃ and 55 ℃ during heating and cooling, respectively, regardless of ZnO length. The bond lengths of V-O and V-V pairs in VO₂/ZnO nanorods were somewhat distorted, and a substantial amount of structural disorder existed in the atomic pairs, compared to those of VO₂ films without ZnO. Resistance from VO₂/ZnO nanorods revealed a sharp MIT near 65 ℃ during heating and a hysteresis behavior. The resistance results suggest that microchannel for charge carriers exist nearly room temperature during cooling. VO₂/ZnO nanorods are quite stable and reproducible so that they can be widely used for practical applications to electronic devices, gas sensors, and ultra-fast switches, as examples.Keywords: metal-to-insulator transition, VO₂, ZnO, XAFS, structural-phase transition
Procedia PDF Downloads 473867 Implementing a Neural Network on a Low-Power and Mobile Cluster to Aide Drivers with Predictive AI for Traffic Behavior
Authors: Christopher Lama, Alix Rieser, Aleksandra Molchanova, Charles Thangaraj
Abstract:
New technologies like Tesla’s Dojo have made high-performance embedded computing more available. Although automobile computing has developed and benefited enormously from these more recent technologies, the costs are still high, prohibitively high in some cases for broader adaptation, particularly for the after-market and enthusiast markets. This project aims to implement a Raspberry Pi-based low-power (under one hundred Watts) highly mobile computing cluster for a neural network. The computing cluster built from off-the-shelf components is more affordable and, therefore, makes wider adoption possible. The paper describes the design of the neural network, Raspberry Pi-based cluster, and applications the cluster will run. The neural network will use input data from sensors and cameras to project a live view of the road state as the user drives. The neural network will be trained to predict traffic behavior and generate warnings when potentially dangerous situations are predicted. The significant outcomes of this study will be two folds, firstly, to implement and test the low-cost cluster, and secondly, to ascertain the effectiveness of the predictive AI implemented on the cluster.Keywords: CS pedagogy, student research, cluster computing, machine learning
Procedia PDF Downloads 90866 Design and Development of Bioactive a-Hydroxy Carboxylate Group Modified MnFe₂O₄ Nanoparticle: Comparative Fluorescence Study, Magnetism and DNA Nuclease Activity
Authors: Indranil Chakraborty, Kalyan Mandal
Abstract:
Three new α-hydroxy carboxylate group functionalized MnFe₂O₄ nanoparticles (NPs) have been developed to explore the microscopic origin of ligand modified fluorescence and magnetic properties of nearly monodispersed MnFe₂O₄ NPs. The surface functionalization has been carried out with three small organic ligands (tartrate, malate, and citrate) having different number of α-hydroxy carboxylate functional group along with steric effect. Detailed study unveils that α-hydroxy carboxylate moiety of the ligands plays key role to generate intrinsic fluorescence in functionalized MnFe₂O₄ NPs through the activation of ligand to metal charge transfer transitions, associated with ligand-Mn²⁺/Fe³⁺ interactions along with d-d transition corresponding to d-orbital energy level splitting of Fe³⁺ ions on NP surface. Further, MnFe₂O₄ NPs show a maximum 140.88% increase in coercivity and 97.95% decrease in magnetization compared to its bare one upon functionalization. The ligands that induce smallest crystal field splitting of d-orbital energy level of transition metal ions are found to result in strongest ferromagnetic activation of the NPs. Finally, our developed tartrate functionalized MnFe₂O₄ (T-MnFe₂O₄) NPs have been utilized for studying DNA binding interaction and nuclease activity for stimulating their beneficial activities toward diverse biomedical applications. The spectroscopic measurements indicate that T-MnFe₂O₄ NPs bind calf thymus DNA by intercalative mode. The ability of T-MnFe₂O₄ NPs to induce DNA cleavage was studied by gel electrophoresis technique where the complex is found to promote the cleavage of pBR322 plasmid DNA from the super coiled form I to linear coiled form II and nicked coiled form III with good efficiency. This may be taken into account for designing new biomolecular detection agents and anti-cancer drug which can open up a new door toward diverse non-invasive biomedical applications.Keywords: MnFe₂O₄ nanoparticle, α-hydroxy carboxylic acid, comparative fluorescence, magnetism study, DNA interaction, nuclease activity
Procedia PDF Downloads 130865 Tape-Shaped Multiscale Fiducial Marker: A Design Prototype for Indoor Localization
Authors: Marcell Serra de Almeida Martins, Benedito de Souza Ribeiro Neto, Gerson Lima Serejo, Carlos Gustavo Resque Dos Santos
Abstract:
Indoor positioning systems use sensors such as Bluetooth, ZigBee, and Wi-Fi, as well as cameras for image capture, which can be fixed or mobile. These computer vision-based positioning approaches are low-cost to implement, mainly when it uses a mobile camera. The present study aims to create a design of a fiducial marker for a low-cost indoor localization system. The marker is tape-shaped to perform a continuous reading employing two detection algorithms, one for greater distances and another for smaller distances. Therefore, the location service is always operational, even with variations in capture distance. A minimal localization and reading algorithm were implemented for the proposed marker design, aiming to validate it. The accuracy tests consider readings varying the capture distance between [0.5, 10] meters, comparing the proposed marker with others. The tests showed that the proposed marker has a broader capture range than the ArUco and QRCode, maintaining the same size. Therefore, reducing the visual pollution and maximizing the tracking since the ambient can be covered entirely.Keywords: multiscale recognition, indoor localization, tape-shaped marker, fiducial marker
Procedia PDF Downloads 124864 Wireless Sensor Network to Help Low Incomes Farmers to Face Drought Impacts
Authors: Fantazi Walid, Ezzedine Tahar, Bargaoui Zoubeida
Abstract:
This research presents the main ideas to implement an intelligent system composed by communicating wireless sensors measuring environmental data linked to drought indicators (such as air temperature, soil moisture , etc...). On the other hand, the setting up of a spatio temporal database communicating with a Web mapping application for a monitoring in real time in activity 24:00 /day, 7 days/week is proposed to allow the screening of the drought parameters time evolution and their extraction. Thus this system helps detecting surfaces touched by the phenomenon of drought. Spatio-temporal conceptual models seek to answer the users who need to manage soil water content for irrigating or fertilizing or other activities pursuing crop yield augmentation. Effectively, spatio-temporal conceptual models enable users to obtain a diagram of readable and easy data to apprehend. Based on socio-economic information, it helps identifying people impacted by the phenomena with the corresponding severity especially that this information is accessible by farmers and stakeholders themselves. The study will be applied in Siliana watershed Northern Tunisia.Keywords: WSN, database spatio-temporal, GIS, web mapping, indicator of drought
Procedia PDF Downloads 485863 A Real Time Monitoring System of the Supply Chain Conditions, Products and Means of Transport
Authors: Dimitris E. Kontaxis, George Litainas, Dimitris P. Ptochos
Abstract:
Real-time monitoring of the supply chain conditions and procedures is a critical element for the optimal coordination and safety of the deliveries, as well as for the minimization of the delivery time and cost. Real-time monitoring requires IoT data streams, which are related to the conditions of the products and the means of transport (e.g., location, temperature/humidity conditions, kinematic state, ambient light conditions, etc.). These streams are generated by battery-based IoT tracking devices, equipped with appropriate sensors, and are transmitted to a cloud-based back-end system. Proper handling and processing of the IoT data streams, using predictive and artificial intelligence algorithms, can provide significant and useful results, which can be exploited by the supply chain stakeholders in order to enhance their financial benefits, as well as the efficiency, security, transparency, coordination, and sustainability of the supply chain procedures. The technology, the features, and the characteristics of a complete, proprietary system, including hardware, firmware, and software tools -developed in the context of a co-funded R&D programme- are addressed and presented in this paper.Keywords: IoT embedded electronics, real-time monitoring, tracking device, sensor platform
Procedia PDF Downloads 168862 Intelligent Rainwater Reuse System for Irrigation
Authors: Maria M. S. Pires, Andre F. X. Gloria, Pedro J. A. Sebastiao
Abstract:
The technological advances in the area of Internet of Things have been creating more and more solutions in the area of agriculture. These solutions are quite important for life, as they lead to the saving of the most precious resource, water, being this need to save water a concern worldwide. The paper proposes the creation of an Internet of Things system based on a network of sensors and interconnected actuators that automatically monitors the quality of the rainwater that is stored inside a tank in order to be used for irrigation. The main objective is to promote sustainability by reusing rainwater for irrigation systems instead of water that is usually available for other functions, such as other productions or even domestic tasks. A mobile application was developed for Android so that the user can control and monitor his system in real time. In the application, it is possible to visualize the data that translate the quality of the water inserted in the tank, as well as perform some actions on the implemented actuators, such as start/stop the irrigation system and pour the water in case of poor water quality. The implemented system translates a simple solution with a high level of efficiency and tests and results obtained within the possible environment.Keywords: internet of things, irrigation system, wireless sensor and actuator network, ESP32, sustainability, water reuse, water efficiency
Procedia PDF Downloads 141861 Black-Box-Optimization Approach for High Precision Multi-Axes Forward-Feed Design
Authors: Sebastian Kehne, Alexander Epple, Werner Herfs
Abstract:
A new method for optimal selection of components for multi-axes forward-feed drive systems is proposed in which the choice of motors, gear boxes and ball screw drives is optimized. Essential is here the synchronization of electrical and mechanical frequency behavior of all axes because even advanced controls (like H∞-controls) can only control a small part of the mechanical modes – namely only those of observable and controllable states whose value can be derived from the positions of extern linear length measurement systems and/or rotary encoders on the motor or gear box shafts. Further problems are the unknown processing forces like cutting forces in machine tools during normal operation which make the estimation and control via an observer even more difficult. To start with, the open source Modelica Feed Drive Library which was developed at the Laboratory for Machine Tools, and Production Engineering (WZL) is extended from one axis design to the multi axes design. It is capable to simulate the mechanical, electrical and thermal behavior of permanent magnet synchronous machines with inverters, different gear boxes and ball screw drives in a mechanical system. To keep the calculation time down analytical equations are used for field and torque producing equivalent circuit, heat dissipation and mechanical torque at the shaft. As a first step, a small machine tool with a working area of 635 x 315 x 420 mm is taken apart, and the mechanical transfer behavior is measured with an impulse hammer and acceleration sensors. With the frequency transfer functions, a mechanical finite element model is built up which is reduced with substructure coupling to a mass-damper system which models the most important modes of the axes. The model is modelled with Modelica Feed Drive Library and validated by further relative measurements between machine table and spindle holder with a piezo actor and acceleration sensors. In a next step, the choice of possible components in motor catalogues is limited by derived analytical formulas which are based on well-known metrics to gain effective power and torque of the components. The simulation in Modelica is run with different permanent magnet synchronous motors, gear boxes and ball screw drives from different suppliers. To speed up the optimization different black-box optimization methods (Surrogate-based, gradient-based and evolutionary) are tested on the case. The objective that was chosen is to minimize the integral of the deviations if a step is given on the position controls of the different axes. Small values are good measures for a high dynamic axes. In each iteration (evaluation of one set of components) the control variables are adjusted automatically to have an overshoot less than 1%. It is obtained that the order of the components in optimization problem has a deep impact on the speed of the black-box optimization. An approach to do efficient black-box optimization for multi-axes design is presented in the last part. The authors would like to thank the German Research Foundation DFG for financial support of the project “Optimierung des mechatronischen Entwurfs von mehrachsigen Antriebssystemen (HE 5386/14-1 | 6954/4-1)” (English: Optimization of the Mechatronic Design of Multi-Axes Drive Systems).Keywords: ball screw drive design, discrete optimization, forward feed drives, gear box design, linear drives, machine tools, motor design, multi-axes design
Procedia PDF Downloads 276