College of Engineering, Pune

About: College of Engineering, Pune is a based out in . It is known for research contribution in the topics: Computer science & Sliding mode control. The organization has 4264 authors who have published 3492 publications receiving 19371 citations. The organization is also known as: COEP.

Arduino UNO and GSM based wireless health monitoring system for patients

Abstract: In India, near about 20% of the total population loses their lives due to interrupted health monitoring system i.e. in most of the hospitals, doctor visits patients either in morning shift or in evening shift or in both shifts. What happens if patient's health becomes critical in between that interval or when a doctor is not available with a patient. The answer is; a patient may lose her\his life. So to avoid this critical situation; we are proposing a smart embedded system device which monitors patients health continuously. This system monitors patients heart rate, body temperature and saline liquid level (if any). If any of the above parameters goes beyond the threshold value, this smart device informs doctors or care taker and ask for corrective actions to save patients life.

Adaptive current differential protection schemes for transmission-line protection

Abstract: Throughout the history of power system protection, researchers have strived to increase sensitivity and speed of apparatus protection systems without compromising security. With the significant technological advances in wide-area measurement systems, for transmission system protection, current differential protection scheme outscores alternatives like overcurrent and distance protection schemes. Therefore, in this paper, we address this challenge by proposing a methodology for adaptive control of the restraining region in a current differential plane. First an error analysis of conventional phasor approach for current differential protection is provided using the concept of dynamic phasor. Subsequently, we extend the methodology for protection of series compensated transmission lines. Finally, we also evaluate the speed versus accuracy conflict using phasorlets. Electromagnetic Transient Program simulations are used to substantiate the claims. The results demonstrate the utility of the proposed approach.

Sliding mode control of active suspension systems using a disturbance observer

Abstract: In this paper a novel active suspension scheme that combines sliding mode control with a disturbance observer is proposed for a quarter car model. The disturbance observer estimates the uncertainties in the system and the unknown road disturbance acting on the unsprung mass. Two control strategies to compensate for the uncertainties and the road disturbance in order to improve the ride comfort are proposed. The stability of the suspension system and the disturbance observer is proved. The efficacy of the method is illustrated by simulation for a vehicle suspension system.

Crop Yield Prediction Using Data Analytics and Hybrid Approach

Abstract: Agricultural data is being produced constantly and enourmosly. As a result, agricultural data has come in the era of big data. Smart technologies contribute in data collection using electronic devices. In our project we are going to analyse and mine this agricultural data to get useful results using technologies like data analytics and machine learning and this result will be given to farmers for better crop yield in terms of efficiency and productivity.

A fuzzy based classification scheme for unconstrained handwritten Devanagari character recognition

Abstract: The large data set and similar structural features of the characters in Devanagari script demand a highly efficient classification and recognition system. This paper presents a novel approach for the recognition of unconstrained handwritten Devanagari characters. The system is based on multi-stage classification scheme. The classification stages categorize the characters into smaller groups. The classification is done using two stages, first stage is based on fuzzy inference system and second stage is based on structural parameters. The fuzzy system improves the classification over crisp classification. The classified characters are passed to the feature extraction stage. The final stage implements feed forward neural network for character recognition. The recognition accuracy achieved by the proposed method is 96.95%.