Qualification :

    • Ph.D. Computer Science and Technology, ME CE, BE CSE

Specialization :

    • Wireless Sensor Networks, Artificial Intelligence, Network Security


    • Department of Computer Engineering

Brief :

Dr. Mininath K. Nighot is a Professor in Computer Science & Engineering department of D. Y. Patil University, Ambi, Pune. He received his Ph.D in Computer Science and Engineering from Shree Sant Gadgebaba Amravati University, Amravati, India in the year 2017. Prior to Ph.D program he graduated from Shree Sant Gadgebaba Amravati University, Amravati, and did his Masters from Savitribai Phule Pune University. He has 18 years of teaching experience and working with DYPCOE since 2018, during this duration he has taught the subjects in the domain of Artificial Intelligence, Network Security, Applied Algorithms, Object Oriented Programming, Data Structure etc. His primary research interests include Wireless Sensor Networks, Artificial Intelligence, Robotics etc. Over the years he has supervised numerous bachelors and masters students. He has published papers in various National / International conferences and journals.

Experience :

    • Total Experience : 18

    • Industrial Experience : Nil

    • International Experience : Nil

    • Academic Experience : 18

Achievements/ Recognitions/ Awards :

    • 1.Mininath Nighot, Ashok Ghatol, Vilas Thakare, “Seeking Target using Self Organized MSN”, 2nd National Conference on Signal Processing, Computer Modeling, Structural and Mechatronics (NCSPCMSM-2K17), Organized by KJ’s Educational Institute, KJ College of Engineering and Management Reserch, Pune, Sponsored by IETE, at Pune, 2017. (Achieved Best Paper Award). 2. Expert talk delivered to DY Patil College of Engineering faculties on “How to write research Proposal” 3.Expert talk delivered to DY Patil College of Engineering faculties on “How to write Scientific/Research Papers”

Professional Memberships :

    • Life Member of ISTE - LM44669

Research Area :

    • Wireless Sensor Network (WSN) is an emerging research area among the researchers due to its large number of real time applications. The target detection and the target tracking are the complex task in WSN, when the target is moving randomly in an unknown environment. Due to the limited searching range and the limited communication range of sensor node, the large number of sensor nodes need to deploy to get the complete coverage of area. The proposed work mainly focuses on energy consumption of three types of network for the target tracking and the target detection problem in area surveillance application. i) Using only Static Sensor Nodes (SSN) approach, in which only dense SSNs are deployed in the WSN, ii) using Only Mobile Sensor Nodes (MSN), in which only few MSNs are used, and iii) using Hybrid Sensor Network (HSN), a combination of both SSN and MSN is proposed. Hybrid WSN is proposed in which both SSN and mobile sensor nodes (MSN) are deployed in searching the area. It works in two modes: 1. The detection mode, and 2. The tracking mode. In the detection mode, MSN’s Movement Prediction Algorithm (MMPA) is designed and implemented. It works using Particle Swam Optimization (PSO) technique to move and decide next move to support mobility of MSN. For tracking mode, three algorithms are designed and implemented namely: Leader Selection Algorithm (LSA), Leader’s Movement Prediction Algorithm (LMPA), and Follower Algorithm. SSNs are deployed, for giving target’s presence in their searching range and sending its own location information to the MSNs. After receiving message, MSNs selects leader, using LSA algorithm. As per the information given by SSN, MSNs travel towards Sender SSN (SSSN) using LMPA and Leader Follower algorithm which uses shortest path algorithm. Once reached to SSSN and if target is found, then it starts target tracking operation to get the information of target’s behavior and movement. If, target is not found, MSNs start searching by MMPA algorithm. To implement first only SSN approach, GPS Based Distributed Communication Protocol for Static Sensor Network (GDCP) algorithm is designed and implemented which finds the shortest path to reach sink node with minimum energy. In this algorithm, sink node is movable. For second only MSN approach, MMPA algorithm is designed and implemented, and for the third HWSN approach, MMPA, LSA, LMPA, and Follower’s Algorithm are designed and implemented.


    • Applied Algorithm, Distributed System High Performance Networks, Wireless Communication, Data Structure and Files, Fundamentals of Data Structure, High Performance Computing, Computer Organization, Programming Paradigms and Methodologies, Advanced Computer Architecture, Information Security System