sensor module
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A majority of the population of developing countries is associated with agriculture directly or indirectly. The liaison of engineering technology and Sustainable Development Goals (SDGs) can build a bridge for farmers to enhance their skills regarding advancements through future generation agriculture trends. The next-generation trends include better soil preparation, intelligent irrigation systems, advanced methods of crop nutrient inspection, smart fertilizers applications, and multi-cropping practices. This work proposes a smart Decision Support System (DSS) that acquires the input parameters based on real-time monitoring to optimize the yield that realizes sustainability by improving per hectare production and lessening water seepage wastage in agribusiness. The proposed model comprises three basic units including an intelligent sensor module, smart irrigation system and controlled fertilizer module. The system has integrated sensors, cloud employing decision support layers, and networking based DSS to recommend cautions for optimum sustainable yield. The intelligent sensors module contains a temperature and humidity sensor, NPK sensor, soil moisture sensor, soil conductivity sensor, and pH sensor to transmit the statistics to the cloud over the internet via Long Range (LoRa) using Serial Peripheral Interface (SPI) communication protocol. Moreover, an android application has been developed for real-time data monitoring according to GPS location and node information (accessed remotely). Furthermore, the DSS contemplates the accessible information from sensors, past patterns, monitoring climate trends and creating cautions required for sustainable fertilizer consumption. The presented results and comparison validate the novelty of the design as it embraces smart irrigation with smart control and smart decision-making based on accurate real-time field data. It is better than existing systems as it transmits the data over the LoRa that is an open-source communication with long-range transmission ability up to several kilometres. The sensor nodes helped in advancing the yield of crops, which resulted in achieving inclusive and sustainable economic goals.

In Hard Disk Drive (HDD) manufacturing, there is always a concern about the cutting defects that are caused by residual cutting chips. Only a small amount of 10 μm chips (act as the air gap) can cause the workpiece to tilt and shift from the correct position, and thus affect the dimension of the workpiece (mainly the Base HDD). For this reason, researchers adapted the adjustable micrometer as a simulation device that resembles the air gap for the design of the Air Gap Sensor Module. The design of experiments using response surface methodology will be studied to confirm the appropriate factors of the prototype. This study reports the optimization of the main factors that affect Air Gap Sensor Module condition: Air Nozzle Diameter 2.303 mm, Air Pressure 0.1 MPa, and Sampling Time 645 ms, which has a high square of the coefficient correlation (R-squared = 99.0%) with a close relationship between gap distance and air pressure. The relationship between these variables is mostly linear. The R-squared error percentage of actual value is less than 0.93% compared to predicted value. The mathematical model results and experimental values were consistent and able to predict response variables. The Air Gap Sensor Module can provide the measurement results in micron ccuracy and displays light and beep to confirm as acceptable or reject gap conditions with the uncertainty of measurement ± 0.001 mm.

Disruptive innovations in data management and analytics have led to the development of patient-centric Healthcare 4.0 from the hospital-centric Healthcare 3.0. This work presents an IoT-based monitoring systems for patients with cardiovascular abnormalities. IoT-enabled wearable ECG sensor module transmits the readings in real-time to the fog nodes/mobile app for continuous analysis. Deep learning/machine learning model automatically detect and makes prediction on the rhythmic anomalies in the data. The application alerts and notifies the physician and the patient of the rhythmic variations. Real-time detection aids in the early diagnosis of the impending heart condition in the patient and helps physicians clinically to make quick therapeutic decisions. The system is evaluated on the MIT-BIH arrhythmia dataset of ECG data and achieves an overall accuracy of 95.12% in classifying cardiac arrhythmia.

The problem of late replacement of infusion mattresses for patients in a medical institution is still common today. It still helps him closely with the nurses' negligence in monitoring the patient's infusion condition. This condition is very dangerous for the patient's health. Therefore the making of infusion monitoring equipment based on NodeMCU esp8266. This tool works by relying on the results of sensor readings that are inserted into the microcontroller which will be processed by NodeMCU. The sensor used in making this system is the sensor module, the sensor reading sensor is the intended emission sensor - in this case, means the drip drops, the sensor will count the number of drops. From the number of drops, it can be used to count the drip infusion. In this study, it can be concluded that the NodeMCU ESP 8266-based infusion monitoring tool using the IR Obstacle sensor component has been successfully made through the functionality test process.

The vision-based approach to mobile robot navigation is considered superior due to its affordability. This paper aims to design and construct an autonomous mobile robot with a vision-based system for outdoor navigation. This robot receives inputs from camera and ultrasonic sensor. The camera is used to detect vanishing points and obstacles from the road. The vanishing point is used to detect the heading of the road. Lines are extracted from the environment using a canny edge detector and Houghline Transforms from OpenCV to navigate the system. Then, removed lines are processed to locate the vanishing point and the road angle. A low pass filter is then applied to detect a vanishing point better. The robot is tested to run in several outdoor conditions such as asphalt roads and pedestrian roads to follow the detected vanishing point. By implementing a Simple Blob Detector from OpenCV and ultrasonic sensor module, the obstacle's position in front of the robot is detected. The test results show that the robot can avoid obstacles while following the heading of the road in outdoor environments. Vision-based vanishing point detection is successfully applied for outdoor applications of autonomous mobile robot navigation.

Automatic Transfer Switch (ATS) is a device that can move the main power source to a backup power source automatically and quickly when the main power source experiences a disturbance or cut-off of supply to the load. In this study, ATS was designed based on the Arduino Nano microcontroller as an automatic control that works based on voltage readings. Using the Arduino Nano microcontroller can facilitate the process of making tools and minimize the use of components. This ATS uses the PZEM-004T voltage sensor module. The voltage sensor module functions to detect and measure the value of the PLN voltage. From the test results, it was found that the time lag between the PLN supply being cut off until the generator was turned on and ready to load was an average of 2.76 seconds. Meanwhile, the time lag when the PLN supply turns on again until the generator supply is cut off and the load supply is again served by PLN is an average of 1.74 seconds. All working status of this ATS panel can be displayed on the LCD indicator, indicator light and analog voltmeter.

According to the development needs of wireless sensor networks, this paper uses the combination of embedded system and wireless sensor network technology to design a network node platform. This platform is equipped with a sports training sensor module to measure the physiological indicators of the ward in real time. The network node sends the collected physiological parameters to a remote monitoring center in real time. First, according to the generation mechanism of the physiological index signal and the characteristics of the physiological index signal, the wireless sensor network analysis and processing method are used to denoise the physiological index signal, and the wireless sensor network package is used to extract the characteristics of the physiological index, indicating different types of respiration. The energy characteristics of the sound physiological index signals are different, which verifies the feasibility of the independent component analysis method for separating the physiological index and the physiological index signal of the heart sound. Secondly, the hardware system of physiological index signal acquisition is designed, and the selection principle of the hardware unit is introduced. At the same time, the system structure of the monitor is designed, and then, the wireless sensor network sensor node is researched, the hardware of the wearable monitor system is designed, and the hardware architecture and working mode based on the single-chip MSP430F149 are given. Finally, the wireless hardware platform includes the following main modules: sensor part, preprocessing circuit module, microprocessing module based on MSP430 low power consumption, wireless transceiver module based on RF chip CC2420, and power supply unit used to provide energy.

The growth in fluidic devices, such as organ-on-chip (OOC) technology, comes with a need for growth in sensing capabilities of key biomolecules to help elucidate changes during the time course of experiments. We developed an on-line, easy-to-assemble, 3D-printed electrochemical sensor module that is magnetically sealed for ease of assembly. The sensor module includes a plug-and-play format for electrochemical sensors made in finger-tight fittings to allow for a wide selection of experimental set-ups and target molecules. Here, we report the feasibility of the sensor module as well as demonstrate its use for electrochemical sensing with integrated thermoplastic electrodes (TPEs). The sensor module withstood over 300 kPa of backpressure and demonstrated reliable performance with TPEs when using cyclic voltammetry (CV) and amperometry under flow conditions. CVs using the ferri/ferrocyanide (K3/4[Fe(CN)6]) redox system demonstrate that the sensor module does not hinder the expected linear response with respect to analyte concentration. Further CVs and amperometry demonstrated the use of the sensor module under flow conditions. Such success in device design and usability is promising for future work using the on-line sensor module with a variety of applications.