Smart fire detection system for building using image processing
Fire detection is the main objective of this project besides surveillance. The aim of the project is too early detection of fire apart from preventive measures to reduce the losses due to fire. The project mainly is based on image processing and Controllers serial communication. In this project, at the user end, the fire images will be feeder in the form of video frames. These images will be further processed by using the software, MATLAB. The proposed system uses RGB and CMY color space. The advantage of using CMY color space is that it can separate the luminance from the chrominance more effectively than RGB color space. Along with this smoke, motion, area detection is also performed using its color characteristics. The proposed system consists of hardware such as Controller, Camera, LED, and Buzzer. There is a camera for surveillance. This camera will give a real-time video output to the user on the laptop or computer via a small GUI-graphic user interface which is to be built in MATLAB. Thus the fire will be detected using this model. In this project, we include some condition regarding fire i.e. small, medium, and high fire with or without the person. If the fire is without person then automatic message sends to fire brigades. And if the fire is med and high with human means any person surrounded by fire or trapped in a fire then automatically message send to fire brigades and Ambulance using Wi-Fi modules.
Published by: Akash Vitthal Thorat, Suyog Shah, Pavan Rajesh Sharma, Baliram Baburao Suryawanshi
Author: Akash Vitthal Thorat
Paper ID: V5I3-1510
Paper Status: published
Published: May 23, 2019
Clustering on uncertain data based on probability distribution similarity using Kullback-Leibler divergence
Cluster analysis is one in all the necessary knowledge analysis strategies and could be a terribly advanced task. it's the art of a sleuthing cluster of comparable objects in massive data sets while not requiring such teams by suggests that options or knowledge information bunch on unsure knowledge could be the toughest task in each modeling similarity between uncertain data objects. The foremost of the previous technique for a bunch unsure knowledge extends partitioning clustering algorithms and Density-based mostly clustering algorithms. These strategies are supported by the geometric distance between two unsure knowledge objects. Such technique unable to handle unsure objects, that are cannot distinguishable by victimization geometric characteristics and Distribution associated with object itself isn't thought-about. likelihood distribution could be the most vital characteristic of the unsure object isn't taking under consideration throughout measurement the similarity between 2 uncertain objects. The very fashionable technique Kullback-Leibler divergence won't to measures the distribution similarity between two unsure knowledge objects. Integrates the effectiveness of KL divergence into each partition and density based mostly bunch algorithms to properly cluster unsure knowledge. Calculation of KL-Divergence is extremely expensive to resolve this drawback by victimization well-liked technique kernel density estimation and use the quick Gauss remodel technique to any speed up the computation to decrease execution time
Published by: Vanashri Shrirang Shinde, C. M. Jadhav
Author: Vanashri Shrirang Shinde
Paper ID: V5I3-1581
Paper Status: published
Published: May 23, 2019
Productivity improvement in tyre manufacturing plant
This paper focuses on studying the production processes at Tyre manufacturing plant in order to understand the current productivity and suggesting the ways to improve the same. In any production processes, the major factors affecting the productivity are the non-value added activities and defects/non- conformities generated plus the rework done to eliminate the defects. DMAIC methodology is used to carry out the study. Initially, the current performance of the system is studied and measured using techniques like Time study and Process Capability. Next techniques like FMEA and Root Cause analysis are implemented to analyze and identify the sources of non-conformities. Improvement in the Loading and Unloading Efficiency is achieved from 58.835% to 100 %. Since 4 seconds were saved for every batch which resulted in saving 940 seconds or 15.677 minutes per shift. This resulted in increasing the batch number from 235 to 245 batches per shift per mixer. Also, the 3M/4M condition is suggested to reduce the major defect from potentially occurring in both Tyre building and Tyre Curing department.
Published by: Kaushik Amonkar, Dr. Jayant K. Kittur
Author: Kaushik Amonkar
Paper ID: V5I3-1408
Paper Status: published
Published: May 23, 2019
Impact of growth medium on siderophore production by Vibrio campbellii: An experimental approach using universal CAS assay
The growth medium is the sole source of nourishment for the bacteria cultured under laboratory conditions. This implies that the growth medium could largely influence the quality and quantity of secondary metabolites produced by the bacterium. Secondary metabolites are the weapons used by bacteria for survival in competitive ecosystems. In this regard, Siderophores are among the vital secondary metabolites of marine bacteria which help them in sourcing the minimal iron essential for their growth and virulence from the marine environment. Among the 11 different growth media evaluated for their impact on Siderophore production by the emerging marine pathogen Vibrio campbellii, MM9 native (minimal salt medium) was found to yield the maximum siderophore units (95.35%). The key factors influencing the growth of V. campbellii were found to be glucose and casamino acid. The determinant factors influencing Siderophore production were found to be glucose and iron-depleted composition of MM9 native medium.
Published by: Archana V., Revathi K., Siva Gayathri Kola, V. P. Limna Mol, Kirubagaran R.
Author: Archana V.
Paper ID: V5I3-1448
Paper Status: published
Published: May 23, 2019
A novel design and implementation of crack pattern analysis using image processing
Nowadays, cracks are more happening due to environmental changes, In the real-time scenario, cracks are very common in a wall, bridge, furniture, railway track. Cracks are the black marks that vanish the civil infrastructure. It indicates the safety status and It is typically developed within a few months or years.
Published by: Shreenidhi, Vinushree G. P., Sindhu K., Mamatha G.
Author: Shreenidhi
Paper ID: V5I3-1550
Paper Status: published
Published: May 23, 2019
Traffic load minimization in software-defined wireless sensor networks
In this paper, we have discussed the problem of traffic and how to solve it using WSN and IoT. As we know IOT is the latest technology and is being used in many sectors nowadays at it very effective. As we know the problem of traffic management is increasing nowadays is big cities which causes many problems like traffic, accidents, and pollution. Management of traffic is very important and a tedious job. There have been many methods used to solve these Problems. Also, the issues like car theft have also increased nowadays, also due to high traffic ambulance also have problems in reaching the hospitals fast. In this paper, we have discussed the technique of solving this problem using IOT. There will be a sensor node and a base node the sensor node will be used to count the traffic in each lane and will send the information to the base node and the base node will take the decision of allocation of them. Also, the base node will have an RFID reader connected which will be continuously Reading for the RFID cards that will be present at the cars and compare it with the database and search for the stolen cars and ambulance and will notify after the stolen car is detected. This will help to solve the traffic management problem the theft problem and the emergency situations for the ambulance.
Published by: Gade Neeta, Rathod V. U.
Author: Gade Neeta
Paper ID: V5I3-1501
Paper Status: published
Published: May 23, 2019
