Microclimate monitoring system for irrigation water optimization using IoT

The new notion of Agri (from ‘Agre’, latin for Land) – Culture (latin for Cultivation) is what made the transition of human race from primitive hunter-gatherers to more civilized and ordered societies. The invention of agriculture can be regarded as a key point in the timeline and dawn of modern civilization as we know it today. With the advent of digital electronics, we are now capable of carefully device systems to make any processes more optimized and generate significantly higher output, this is also true for the agriculture sector and many works are carried out recently aimed towards this objective and even created a new domain of precision agriculture. In this research work, an IoT-based system was developed that enables the farmers to monitor various micro-climatic parameters and assess the irrigation water requirement. The soil moisture and temperature were sensed with the aid of sensors and were fed to the LoRA system, in the receiver side, data is analyzed for the estimation of evapotranspiration. The global evapotranspiration was estimated using Cropwat software. The sensor data were analyzed using Mcguinnes-Bordne formulation and the outcome of this research work paves the way towards the estimation of the evapotranspiration in the microclimate environment

A study on ECG signal characterization and practical implementation of some ECG characterization techniques

The role of ECG is pivotal in medical field for the analysis of cardiac physiology and abnormalities. The interpretation of ECG signal is performed by signal processing algorithms for diagnosis of cardiac diseases. This work analyses filtering approaches, component extraction, classification and compression algorithms for the ECG signal. The portable ECG systems are also analysed; results and discussion comprises of IIR notch filter for the removal of power line interference, hybrid wavelet filter for removal of baseline wander, FFT algorithm for R peak detection and hybrid filtering approach for the detection of P, QRS and T components. The outcome of this research work is an aid for researchers developing novel algorithms in ECG filtering, segmentation and classification. The algorithms are developed in Matlab 2015b and tested on fantasia database data sets