Abstract-This paper presents a method for fetal heart rate estimation from an abdominal electrocardiogram (ECG) signal based on adaptive filter analysis using least mean square (LMS) adaptive filtering algorithm in order to determine the health status of a baby in its mother's womb. The fetal ECG signal is extracted from abdominal ECG containing other sources of interference using the maternal ECG signal obtained from mother's chest cavity as the reference signal. Interference/noise model used for this work include the power-line noise, the white noise and the unwanted propagating maternal ECG signal. Thereafter, the heart rate is estimated using an automated peak voltage measurement algorithm at 75 percent threshold voltage. It is found that irrespective of the estimated heart rate of the baby, 100 percent estimation is achieved at signal-to-noise ratio (SNR) greater than or equal to -31dB.

No abstract

Aims: To simulate and construct a solar powered smart irrigation system using Blynk Mobile App. Study Design: Experimental design through simulation studies and internet of things. Place and Duration of Study: Department of Physics, Nasarawa State University Keffi, Nigeria, between July 2021 and March 2022. Methodology: The system was simulated using Proteus ISIS Version 8.6. It consists of two main units that is transmitter and receiver. The transmitter consists of a sensor circuit that senses the soil moisture, humidity and temperature. Then the Node MCU microcontroller collects the data and sent to the Blynk Mobile App (Receiver). The circuit was tested at two different conditions of the soil; Wet soil and Dry soil. Results: Output performance analysis when the water level in soil (Moisture) was high, indicated Temperature value 28.3°C, Humidity 72%, and the Pump was OFF. When the water level in soil was mild, temperature was 60°C, Humidity 68%, and pump was turned ON. The pump is activated to switch ON as far as the water reservoir is having enough water and will switch OFF when the required level of moisture in the soil is achieved. The solar power ensured constant power supply, while the Blynk Mobile App ensured real time data monitoring by the Farmer even when he is far away from the farm. Conclusion: This system is an improve irrigation system that supports low water and electricity consumption as well as efficient monitoring for increase farmers’ output.

No abstract

No abstract