Sensor Reading Errors Research Articles

Development of Nutrient Control System in Plant Factory based on Growth Phases of Romaine Lettuce (Lactuca sativa var. longifolia)

Nutrient is one of the conditions controlled in a plant factory. Nutrient control must be based on the plant growth phase, but previous research has shown shortcomings in this area. This study aims to develop a nutrient control system in a plant factory based on the plant growth phase, specifically using Romaine lettuce. The research method used is the experimental method, with research stages including system design (controller modification, programming, and TDS sensor calibration testing) and system performance testing. The TDS sensor calibration test results showed an R² of 0.9999, indicating that the TDS sensor readings are very close to those of the TDS meter. The system performance test results showed that the developed system works well in controlling nutrient levels based on the growth phase of Romaine lettuce. The planting process lasted 30 days, from October 13, 2023, to November 11, 2023, with a total of 2,697 data points recorded by Antares. Nutrient requirements were adjusted per the growth phase of Romaine lettuce, with set points in the first to fourth weeks being 500 PPM, 600 PPM, 700 PPM, and 800 PPM, respectively. The average nutrient levels recorded in the first week were 518 PPM, 623 PPM in the second week, 721 PPM in the third week, and 820 PPM in the fourth week. The TDS sensor accuracy test results showed an R² of 0.9998, indicating that the TDS sensor performed well in controlling nutrient levels during the system testing, with an average TDS sensor reading error of only 1.17%. During the planting process, the total amount of nutrients added for each of nutrients A and B was 210.10 ml, with the total operating time of the control components being 314.34 seconds for each peristaltic pump of nutrients A and B.

MXene-Coated Ion-Selective Electrode Sensors for Highly Stable and Selective Lithium Dynamics Monitoring.

Lithium holds immense significance in propelling sustainable energy and environmental systems forward. However, existing sensors used for lithium monitoring encounter issues concerning their selectivity and long-term durability. Addressing these challenges is crucial to ensure accurate and reliable lithium measurements during the lithium recovery processes. In response to these concerns, this study proposes a novel approach involving the use of an MXene composite membrane with incorporated poly(sodium 4-styrenesulfonate) (PSS) as an antibiofouling layer on the Li+ ion selective electrode (ISE) sensors. The resulting MXene-PSS Li+ ISE sensor demonstrates exceptional electrochemical performance, showcasing a superior slope (59.42 mV/dec), lower detection limit (10-7.2 M), quicker response time (∼10 s), higher selectivity to Na+ (-2.37) and K+ (-2.54), and reduced impedance (106.9 kΩ) when compared to conventional Li+ ISE sensors. These improvements are attributed to the unique electronic conductivity and layered structure of the MXene-PSS nanosheet coating layer. In addition, the study exhibits the long-term accuracy and durability of the MXene-PSS Li+ ISE sensor by subjecting it to real wastewater testing for 14 days, resulting in sensor reading errors of less than 10% when compared to laboratory validation results. This research highlights the great potential of MXene nanosheet coatings in advancing sensor technology, particularly in challenging applications, such as detecting emerging contaminants and developing implantable biosensors. The findings offer promising prospects for future advancements in sensor technology, particularly in the context of sustainable energy and environmental monitoring.

Heart Rate and Body Temperature Tracking Application Based on Fuzzy Logic

Temperature and heart rate are indicators of health. It is necessary to monitor heart rate and body temperature to prevent the spread of a virus or disease. In most cases, heart rate and body temperature are monitored independently, and the patient cannot view a record of previous examinations. This study uses fuzzy logic to develop an application for monitoring heart rate and body temperature. It can monitor heart rate and body temperature in real-time, store a history of previous examinations, and use fuzzy logic to diagnose body conditions based on heart rate and body temperature data. Based on test results, the sensor reading error rate for heart rate is minimal at 0.68 and for body temperature at 0.18. The accuracy of fuzzy diagnosis of the patient's body condition is one hundred percent. The performance indicator for the application is excellent, the completion rate is 100 percent, and the time-based efficiency is 93%. The results of the user satisfaction test indicate that most users are pleased with the application's usability. The average value for measuring user satisfaction is 80%, with the highest result of the five measurement criteria being 89.6% for the ease-of-use criterion.

Rancang bangun sistem monitoring dan kontrol pH air untuk budidaya ikan lele

One of the water quality parameters that are important to consider in fish farming is pH. Unstable pH conditions can cause a decrease in water quality and cause fish to harvest less than optimal yields. Under certain conditions, there is an extreme change in the pH value, so it needs to be normalized again. This study aims to design a monitoring and control system of pH for catfish farming. The control system consisted of an SKU SEN0161 type pH sensor, equipped with two pumps to automatically flow alkaline and acidic pH solutions. The design method used was the prototyping method, i.e. Listen to Customer (Design criteria collection), Design and Build Prototype, and Test Drive and Evaluation. Based on the static characteristic test on the pH sensor, it was found that the pH sensor reading error was 0.11 with a deviation of 0.03. A small error value indicates that the sensor has high accuracy and a little deviation value indicates that the sensor has a high level of precision. For the repeatability test with an interval measurement of 5 minutes, the sensor measurement had a deviation of 0.01. The performance test of the pH control system showed that the system had been able to control the pH according to the set point (6 and 7.5), both under acidic conditions (pH 5.4) and under alkaline conditions (pH 8). The system had also been able to store and display data on Android devices in real-time (24 hours non-stop) via an internet connection, making it easier to monitor by users. It was also found that catfish can grow well at pH 6.5-8.

Implementation of Lora for Controlling and Monitoring Broiler Cage Temperature

A system for controlling the temperature of broilers cages has been made with LoRa data communication. The purpose of this research is to make a prototype of a control system for monitoring and controlling the temperature of broiler controlled by a microcontroller with LoRa communication. The results of measuring system performance are indicated by the DHT11 sensor reading error occurs when the temperature is 36,37 °C and 38 °C by 1.03%. The device that can connect to LoRa is 320 m in Line of Sight (LOS) conditions and 52 m in Non Line of Sight (NLOS) conditions. Overall the tool can function well. Suggestions for further research, an Internet of Things (IoT) based monitoring system can be added using a mobile application.

Fuzzy System to Assess Dangerous Driving: A Multidisciplinary Approach.

Dangerous driving can cause accidents, injuries and loss of life. An efficient assessment helps to identify the absence or degree of dangerous driving to take the appropriate decisions while driving. Previous studies assess dangerous driving through two approaches: (i) using electronic devices or sensors that provide objective variables (acceleration, turns and speed), and (ii) analyzing responses to questionnaires from behavioral science that provide subjective variables (driving thoughts, opinions and perceptions from the driver). However, we believe that a holistic and more realistic assessment requires a combination of both types of variables. Therefore, we propose a three-phase fuzzy system with a multidisciplinary (computer science and behavioral sciences) approach that draws on the strengths of sensors embedded in smartphones and questionnaires to evaluate driver behavior and social desirability. Our proposal combines objective and subjective variables while mitigating the weaknesses of the disciplines used (sensor reading errors and lack of honesty from respondents, respectively). The methods used are of proven reliability in each discipline, and their outputs feed a combined fuzzy system used to handle the vagueness of the input variables, obtaining a personalized result for each driver. The results obtained using the proposed system in a real scenario were efficient at 84.21%, and were validated with mobility experts’ opinions. The presented fuzzy system can support intelligent transportation systems, driving safety, or personnel selection.

Design and Development of Water Distribution Monitoring System in Regional Drinking Water Companies (PDAM) Based On Internet Of Things

The purpose of this study is to create a prepaid PDAM clean water distribution system using a microcontroller based on the Internet of Things (IoT). The hardware used to realize the system consists of ultrasonic sensors, water flow sensors, relays, LCD buzzers and Arduino. ESP 8266 01 for delivery to the Thingspeak app. From the test results obtained HC-SR04 ultrasonic sensor reading error occurs when the water level is low and too high, the maximum measurable water level is 95%. When calculating the comparison between the water discharge that is read by the sensor and that measured by the measuring cup, the results are always not the same. The error when testing the water flow sensor at the water level is less than 49% this is influenced by the speed of the water fired by the pump, where the pump will be under low pressure when the water level is below that value. The system can monitor data readings from the water flow sensor using the ESP8266 monitored on the thinkspeak web server using a smartphone. Overall the tool can function well.

Analysis of Air Temperature and Humidity in Kedunggalar Against BMKG Data Based on DHT11 Sensor

This research was conducted to compare the temperature and humidity data presented by the BMKG against realtime data based on the DHT11 sensor readings in Kedunggalar, Ngawi. Data was collected for 14 days (8-21 September 2020) at the same time interval between 07-10 AM according to the data update on the BMKG website. Temperature and humidity readings are recorded periodically with the DHT11 sensor every second for one minute, so that 60 data generated every one day. The average temperature and humidity data produced by the DHT11 sensor is 29.18 °C and 68.16% with a comparison of the average data from the BMKG website 28.79 °C and 65.36%. So that from the comparison of direct measurements of DHT11 and from the website it has a sensor reading error against a temperature of 1.59 °C and a humidity of 5.24%. The conclusion is that the measurement of temperature and humidity in Kedunggalar with the DHT11 sensor is very valid against the data on the BMKG website. Even though the humidity exceeds the accuracy limit of the DHT11 sensor which is a maximum tolerance value of 5%, on the other hand the temperature reading is very accurate because the tolerance value is less than 2 °C.

IMPLEMENTASI INTERNET OF THINGS (IOT) DALAM SISTEM PEMANTAUAN SERTA KONTROL SUHU DAN PAKAN AYAM PETELUR KANDANG TERTUTUP

The global pandemic that has attacked Indonesia has had a negative impact on many sectors of life. In the food strength sector, many livestock producers have experienced a decline in income and production. In an effort to overcome the risks and impacts that are more severe, the author makes a tool with a monitoring and control system in a closed chicken coop as an effort to increase the quality and quantity of eggs from laying hens. This tool uses an ESP32 controller with a user interface through the Blynk application over a WiFi network based on the Internet of Things. The monitoring function of this tool is for monitoring temperature, humidity, and light intensity in the cage. While the control function that is run on this tool is a function of controlling the volume of drinking water for poultry, remaining poultry feed, and the temperature in the cage which is regulated by flowing cold or hot air in each room of the temperature control box according to the temperature set desired by the user. Based on the test results, this system has a good success rate with a sensor reading error value of not more than 5%.

Performance and energy aware robust specification of control execution patterns under dropped samples

Embedded control systems are prevalent in a multitude of domains such as automotive, avionics, industrial control etc. For such systems, robustness against non-idealities of the compute platform created by situations such as hardware level transient faults (memory errors, sensor reading errors), network packet drops, late arrival of messages etc., is needed to be ensured at the design level. In traditional regular periodic execution of control loops, such guarantees are obtained by oversampling the plant, which requires extra rounds of sensing, control law computation, and actuation. One possible measure for reducing such over-provisioning of computing and communication resources is allowing occasional drops in the execution leading to better resource management as well as energy efficiency. This work showcases a methodology for deriving window-based bounds on possible drops in control loop executions while assuring formal performance guarantees even in the presence of platform-level non-idealities. Derivation of such relaxation bounds in terms of control loop executions help in deciding energy efficient scheduling solutions for low-power resource-constrained embedded control platforms while retaining control performance. The present work provides a structured methodology for deriving performance-aware control execution patterns given an energy-budget and uncertainty specification of the platform executing a set of embedded control loops.

Prototype Traffic Light Design Based Wireless Sensor Network With Multihop Topology

Increasing number of vehicles there are not combining by the increase highway facilities and means of adequate traffic, creating traffic jams can not be avoided. Therefore, it needs a traffic light system which can change the duration adaptive, so delays in traffic flow can be parsed automatically. In this thesis constructed an traffic light prototype that can change the duration of the traffic lights adaptively according to the conditions of real-time flow of the street using a detector such as a HMC5883L compass sensor. With a wireless sensor network and multihop topologies in terms of the system is easy to apply, because it does not require the transmission line in the form of cables and sensors can be added the number and spacing range. The main components used are Arduino Uno, Arduino Mega, XBee and HMC5883L compass sensors. Compass sensor detects the presence of vehicles by calculating magnitude value in the form of interference with Earth's magnetic field caused by cars metal, so the sensor nodes can send information pathways state conditions in the one intersection to the coordinator via another sensor nodes using xbee in multihop topologies. The results obtained after testing is setting plan to address the inequality of delay on the traffic system can work well with the sensor reading error 0.09% within a period of 2 minutes and the application topology multihop use the traffic light system can expand the detection range 400 m. But the number of hops is used affects the packet loss is greater, namely 0.192% at a distance of 200 m.

Systematic Prioritization of Sensor Improvements in an Industrial Gas Supply Network

The paper analyzes the impact of the sensor reading errors on parameters that affect the production costs of a leading US industrial gas supply company. For this purpose, a systematic methodology is applied first to determine the relationship between the system output and input parameters and second to identify the assigned input sensors whose readings need to be improved in a prioritized manner based on the strength of those input-output relationships. The two main criteria used to prioritize these sensors are the decrease in production costs and the decrease in production costs’ volatility obtained when the selected sensor’s precision is improved. To illustrate the effectiveness of the proposed approach, we first apply it to a simplified version of the real supply network model where the results can be readily validated with the simulated data. Next, we apply and test the proposed approach in the real supply network model with historical data.

SmartPhoto: A Resource-Aware Crowdsourcing Approach for Image Sensing with Smartphones

Photos obtained via crowdsourcing can be used in many critical applications. Due to the limitations of communication bandwidth, storage, and processing capability, it is a challenge to transfer the huge amount of crowdsourced photos. To address this problem, we propose a framework, called SmartPhoto , to quantify the quality (utility) of crowdsourced photos based on the accessible geographical and geometrical information (called metadata ) including the smartphone's orientation, position, and all related parameters of the built-in camera. From the metadata, we can infer where and how the photo is taken, and then only transmit the most useful photos. Four optimization problems regarding the tradeoffs between photo utility and resource constraints, namely Max-Utility, online Max-Utility, Min-Selection, and Min-Selection with $k$ -coverage, are studied. Efficient algorithms are proposed and their performance bounds are theoretically proved. We have implemented SmartPhoto in a testbed using Android based smartphones, and proposed techniques to improve the accuracy of the collected metadata by reducing sensor reading errors and solving object occlusion issues. Results based on real implementations and extensive simulations demonstrate the effectiveness of the proposed algorithms.

Thermal sensor allocation for 3DICs using three dimensional thermal sensors

Stacking active layers leads to increased power density and overall higher temperatures in a three dimensional integrated circuit (3DIC). Thermal sensors are therefore crucial for run-time thermal management of 3DICs. A thermal sensor allocation method customized for 3DICs that utilizes ring oscillator based 3D sensors is introduced in this paper. A new 3D thermal map modeling method that facilitates efficient and very fast analyses is embodied in this thermal sensor distribution algorithm. Our results indicate that for a 4-layer stacked 3DIC, consisting of two layers of quad-core processors and one layer of L2 cache and one layer of main memory, less than 3.58% in maximum sensor reading error can be accomplished with a 53× speedup in the thermal evaluation time and thermal sensor distribution algorithm implementation.

A Dynamic Evidential Fusion Network for Decision Making in Multi- Robot System

In smart environments, a multi-robot system is difficult to achieve a high confidence level of information for reliable decision making. The pieces of sensed information obtained from a multi-robot system have different degrees of uncertainty. Generated contexts about the situation of the environment can be conflicting even if they are acquired by simultaneous operations. In particular, unpredictable temporal changes in sensory information reduce the confidence level of information then lead to wrong decision making. In order to solve this problem, we propose a reasoning method based on Dynamic Evidential Fusion Network (DEFN). First, we reduce conflicting information in multi-sensor networks using Evidential Fusion Network (EFN). Second, we improve the confidence level of information using Temporal Belief Filtering (TBF) and Normalized Weighting technique. We distinguish a sensor reading error from sensed information. Finally, we compare our approach with a fusion process based on Dynamic Bayesian Networks (DBNs) using paired observations so as to show the improvement of our proposed method.

Stochastic analysis of a novel force sensor based on bifurcation of a micro-structure

In this paper, the stochastic dynamics of a novel sensing micro-mechanism is investigated. The structure of the micro-mechanism includes a micro-bridge and two equally spaced parallel electrodes on either side. The sensing scheme is based on the detection of the bifurcation of the equilibrium position of the micro-bridge as the axial force of the micro-bridge and the applied voltage to the electrodes change. An analytical model is developed that takes into account the mechanical and electrostatic domains nonlinearities. The behavior of the mechanism is investigated in time domain. The uncertainty in the operating condition, hence the dynamic behavior, of the micro-mechanism is studied using a statistic approach. Although, the dynamic model demonstrates significant deviation from the static model, the narrow statistical distribution of the sensor reading error indicates that the sensor can be easily calibrated for practical purposes. The advantage of this sensor is that it provides very high sensitivity, in the order of 2 mV / μ N , while eliminating the need for permanent oscillation and vacuum encapsulation of the sensing structure. These advantages lead to improved fatigue-life of the sensor as well as the power consumption. As the sensor transduces the force into a voltage reading, measurements can be performed accurately with relatively simple electronics. The result presented in this work provides improved estimation of parameters measured using this sensing micro-mechanism.

A New Method for Measuring Straightness and Yawing Motion Errors of a Linear Slide

In this paper, an on-machine Fourier five-sensor (F5S) measurement method is developed using Fourier series and sensor integration techniques to determine the straightness and yawing motion errors of a linear slide. The profile of the slide is also determined in this error separation technique. The method is an extension of the previous Fourier three-sensor (F3S) method (Fung, E. H. K., and Yang, S. M., 2000, “An Error Separation Technique for Measuring Straightness Motion Error of a Linear Slide,” Meas. Sci. Technol., 11, pp. 1515–1521; Yang, S. M., Fung, E. H. K., and Chiu, W. M., 2002, “Uncertainty Analysis of On-Machine Motion and Profile Measurement With Sensor Reading Errors,” Meas. Sci. Technol., 13, pp. 1937–1945) by including the effects of yawing error in the straightness motion error and profile measurements. The principles and operation of the F5S measurement method are described. The uncertainty analysis of the method in the presence of a sensor reading error is studied both in the frequency domain and the spatial domain. The spatial domain parameter is first optimized to yield the 12 possible sensor configurations and the final configuration is chosen based on the frequency domain parameter values. The method is evaluated by computer simulation where the simulated sensor outputs are derived from the predefined profile, straightness, and yawing motion errors. By comparing the calculated results with the input data, the F5S method is found to be superior to the F3S method as far as accuracy is concerned. The results reported in this simulation study not only confirm the feasibility of the F5S method but also encourage the author to perform an experimental study in the near future.

Uncertainty analysis of on-machine motion and profile measurement with sensorreading errors

In this paper, the novel error separation technique (Fung E H K and Yang S M2000 Meas. Sci. Technol. 11 1515–21) is evaluated by the uncertainty analysiswhen the measurement is subject to sensor reading errors. The variance of theresulting profile estimation error is investigated both in the frequencydomain and in the spatial domain. Theoretical analysis and computersimulation reveal that the profile estimation error, though adversely affected bythe sensor noise, is not cumulative in the sense that the error will notbuild up as a result of increasing the number of sample points as in thetwo-step method (Tanaka H and Sato H 1986 Trans. ASME, J. Eng. Ind. 108176–82). Experiments are also performed to confirm the above finding.