Krishnaraj M.
Krishnaraj M. has a total of 7 co-authors. Here are the top co-authors by number of shared publications:
- G. Sreelekshmy Pillai
NSS College of Engineering (Affiliated to APJ Abdul Kalam Technological University, Kerala, India)
1 shared publication - Jeberson Retna Raj
Sathyabama Institute of Science and Technology
1 shared publication - K S Abhilash
Managing Director EduCorp Centre for Research and Advanced Studies Pvt. Ltd. Thiruvananthapuram, Kerala
1 shared publication - Maithili Shailesh Andhare
Department of Electronics Communication Engineering, Bharath Institute of Higher Education and Research, Chennai 600073, India
1 shared publication - Triveni Lal Pal
National Institute Of Technology Hamirpur
1 shared publication - V. Jayaram
Edzumo Pvt Ltd
1 shared publication
Latest Publications
- Open Access
- 1 January 2024
- Published by Engineering and Technology Publishing in Journal of Advances in Information Technology
- Vol. 15 (1) , 118-126
Face Identification Based on Active Facial Patches Using Multi-Task Cascaded Convolutional Networks
- 1 January 2024
- Published by Engineering and Technology Publishing in Journal of Advances in Information Technology
- Vol. 15 (1) , 118-126
Open AccessFace Identification Based on Active Facial Patches Using Multi-Task Cascaded Convolutional Networks
- Open Access
- 16 June 2022
- Published by Universidad Tecnica de Manabi in International journal of health sciences
- p. 3158-3169
Design and implementation of wireless sensor network for environmental monitoring
Wireless Sensor Networks (WSN) are being developed in the agriculture and weather station sectors to monitor and manage a number of objects. Sensor network hardware platforms are low-power embedded systems featuring a variety of sensors, such as on-board sensors and analogue I/O ports for adding sensors. The design of genuine environmental monitoring and communication systems is greatly aided by the creation of a WSN. A WSN is a collection of sensors that are geographically spread and specialized for monitoring and recording environmental variables and storing the findings in a central location. Limited power consumption as sensor nodes works on batteries, Nodes are mobile opposed to conventional wires, Usage in harsh environment, Nodes can be deployed in any fashion over an area, Easy to use and multi-layer design operation these are the main characteristics of WSN. Limits imposed on the energy storage device by their applications and deployment settings are less relevant to WSN environment-monitoring applications than controlling power consumption and optimizing data transmission. A WSN is used to record real-time traffic and environmental data in order to develop descriptive and predictive models for determining the optimum routes to reduce traffic congestion and, as a result, urban pollution. C
- 16 June 2022
- Published by Universidad Tecnica de Manabi in International journal of health sciences
- p. 3158-3169
Open AccessDesign and implementation of wireless sensor network for environmental monitoring
Wireless Sensor Networks (WSN) are being developed in the agriculture and weather station sectors to monitor and manage a number of objects. Sensor network hardware platforms are low-power embedded systems featuring a variety of sensors, such as on-board sensors and analogue I/O ports for adding sensors. The design of genuine environmental monitoring and communication systems is greatly aided by the creation of a WSN. A WSN is a collection of sensors that are geographically spread and specialized for monitoring and recording environmental variables and storing the findings in a central location. Limited power consumption as sensor nodes works on batteries, Nodes are mobile opposed to conventional wires, Usage in harsh environment, Nodes can be deployed in any fashion over an area, Easy to use and multi-layer design operation these are the main characteristics of WSN. Limits imposed on the energy storage device by their applications and deployment settings are less relevant to WSN environment-monitoring applications than controlling power consumption and optimizing data transmission. A WSN is used to record real-time traffic and environmental data in order to develop descriptive and predictive models for determining the optimum routes to reduce traffic congestion and, as a result, urban pollution. C