Punit Gupta

IoT based smart healthcare kit

The paper presents the design and implementation of an IOT-based health monitoring system for emergency medical services which can demonstrate collection, integration, and interoperation of IoT data flexibly which can provide support to emergency medical services like Intensive Care Units (ICU), using a INTEL GALILEO 2ND generation development board. The proposed model enables users to improve health related risks and reduce healthcare costs by collecting, recording, analyzing and sharing large data streams in real time and efficiently. The idea of this project came so to reduce the headache of patient to visit to doctor every time he need to check his blood pressure, heart beat rate, temperature etc. With the help of this proposal the time of both patients and doctors are saved and doctors can also help in emergency scenario as much as possible. The proposed outcome of the project is to give proper and efficient medical services to patients by connecting and collecting data information through health status monitors which would include patients heart rate, blood pressure and ECG and sends an emergency alert to patients doctor with his current status and full medical information.

IoT based Smart Home design using power and security management

The paper presents the design and implementation of an Ethernet-based Smart Home intelligent system for monitoring the electrical energy consumption based upon the real time tracking of the devices at home an INTEL GALILEO 2ND generation development board, which can be used in homes and societies. The proposed system works on real time monitoring and voice control, so that the electrical devices and switches can be remotely controlled and monitored with or without an android based app. It uses various sensors to not only monitor the real time device tracking but also maintaining the security of your house. It is monitored and controlled remotely from an android app using the Internet or the Intranet connectivity. The proposed outcome of the project aims as multiple benefits of saving on electricity bills of the home as well as keep the users updated about their home security with an option of controlling the switching of the devices by using their voice or simple toggle touch on their smartphone, and last but most importantly, monitor the usage in order to conserve the precious natural resources by reducing electrical energy consumption.

IoT based power efficient system design using automation for classrooms

The paper presents the design and implementation of an Ethernet-based intelligent automated system for conserving electrical energy using a INTEL GALILEO 2ND generation development board, which can be used in large organizations like a University or an office. The proposed system works on automation, so that the electrical devices and switches can be remotely controlled and monitored without any human intervention. It uses the available infrastructure in a classroom that includes surveillance camera and Ethernet connectivity so as to minimize the cost criteria. It is monitored and controlled remotely from a web server located at the control room using the Internet or the Intranet connectivity. The proposed outcome of the project aims as multiple benefits, saving on electricity bills of the University or any other organization it is deployed in, eliminating human involvement and manpower which is often required to manually toggle the lights and electrical device on/off, and last but most importantly, conserve the precious natural resources by reducing electrical energy consumption.

Load and Fault Aware Honey Bee Scheduling Algorithm for Cloud Infrastructure

Cloud computing a new paradigm in the field of distributed computing after Grid computing. Cloud computing seems to me more promising in term of request failure, security, flexibility and resource availability. Its main feature is to maintain the Quality of service (QoS) provided to the end user in term of processing power, failure rate and many more .So Resource management and request scheduling are important and complex problems in cloud computing, Since maintaining resources and at the same time scheduling the request becomes a complex problem due to distributed nature of cloud. Many algorithms are been proposed to solve this problem like Ant colony based, cost based, priority based algorithms but all these algorithm consider cloud environment as non fault, which leads to degrade in performance of existing algorithms. So a load and fault aware Honey Bee scheduling algorithm is proposed for cloud infrastructure as a service(IaaS). This algorithm takes into consideration fault rate and load on a datacenter to improve the performance and QoS in cloud IaaS environment.

IoT based intelligent billboard using data mining

The paper presents the design and implementation of an intelligent advertising system using Raspberry Pi B+ v1.2 development board, RFID and display panels integrated over a network. This system can be used in multi retail stores, malls and shopping complexes. The proposed system works on performing data mining and trend analysis over sales, inventory data which is collected in real time by using POS system implemented using RFID tags attached to products. The display panels(billboards) will be placed at strategic locations. The proposed outcome of the project aims to provide better offers and deals to customers without targeting them individually, rather using a segmented approach.

Handling Data Integrity Issue in SaaS Cloud

Cloud computing is a technology that being widely adopted by many organizations like Google, Microsoft etc in order to make the resources available to multiple users at a time over the internet. Many issues are identified due to which cloud computing is not adopted by all users till now. The aim of this paper is to analyze the performance of the encryption algorithms in order to improve the data integrity in SaaS cloud. The proposed modified algorithm encrypts the data from different users using cryptographic algorithms namely: RSA, Bcrypt and AES. The algorithm is selected by user based on the level of security needed to be applied to the user’s data. Performance analysis of the given framework and algorithm is done using CloudSim. From our obtained results this could be easily found that the time taken for encryption of data using the discussed framework and proposed algorithms is much less in comparison to various other techniques.

Trust and deadline aware scheduling algorithm for cloud infrastructure using ant colony optimization

Cloud computing is now trending and more popular in these days for the computation and adopted by many companies like Google, Amazon, Microsoft etc., As the cloud size increases with increase in number of data center power consumption over a data center increases. As number of request over the data center increase with increase in load and power consumption of the data center. So the requests need to be balanced in such manner which having more effective strategy for utilization of resources and reduction in power consumption. Request balancing in such manner without having knowledge of load over server maximize resource utilization but also increasing power consumption at server. So to overcome these issues in cloud Infrastructure as a service (IaaS), we have proposing a trust based scheduling algorithm using ant colony to minimize the load, OoS of the system. Proposed algorithm has proven to have better performance in term of load and reduced request failure as compared to previously proposed scheduling balancing algorithm for cloud IaaS.

Power aware resource virtual machine allocation policy for cloud infrastructure

Cloud computing is now trending and more popular in these days for the computation and adopted by many companies like google, amazon, Microsoft etc., As the cloud size increases with increase in number of data center power consumption over a data center increases. As number of request over the data center increase with increase in load and power consumption of the data center. So the requests need to be balanced in such manner which having more effective strategy for utilization of resources and reduction in power consumption. A recent survey on cloud computation shows that the power consumption of a server, increasing in a linear way due to utilization of resource (processors). Request balancing in such manner without having knowledge of load over server maximize resource utilization but also increasing power consumption at server. So to overcome these issues in cloud Infrastructure as a service (IaaS), we have proposing a load balancing algorithm to minimize the load, power consumption and cost over a server. Proposed algorithm has proven to have better performance in term of load and power efficiency as compared to previously proposed load balancing algorithm for cloud IaaS.

Safe Sole Distress Alarm System for Female Security Using IoT

The paper presents development of a sole for protection of female using Arduino microcontroller which is named as ‘SAFE SOLE’. The research goal of safe sole is to develop a safety device/tool for females in the event they might face any danger. The advantages of automaticity of safe sole are hands-free user independence; it uses GPS and GSM to ping user’s location automatically. The device is programmed in such a way that it recognizes defined movements as tapping forcefully three times on ground or any abnormal/vigorous movement/gait of user instantaneously and pings the distress signal and the location to relevant authorities and saved contacts, and additionally taking countermeasures—triggering of siren. In view of this, aforementioned system is a source of developing a product for general population which helps in maintaining the safety of the user by eliminating the involvement of user to initiate any procedural activities against any situation which user might feel in danger.

QoS Aware Grey Wolf Optimization for Task Allocation in Cloud Infrastructure

Cloud computing is a reliable computing platform for large computationally intensive or data-intensive tasks. This has been accepted by many industrial giants of the software industry for their software solutions; companies like Microsoft, Accenture, Ericson, etc. have adopted cloud computing as their first choice for cheap and reliable computing. By increasing the number of clients adopting this, there is a requirement of much more cost-efficient and high-performance computing for more trust and reliability among the client, and the service providers to guarantee cheap and more efficient solutions. So the tasks in cloud need to be allocated in an efficient manner to provide high resource utilization and least execution time for high performance, and at the same time provide least computational execution cost. We have proposed a learning-based grey wolf optimization algorithm for task allocation to reduce the request time and scheduling time to improve QoS (Quality of Service). Proposed algorithm has been inspired from behaviour of wolfs hunting in real world with a unique technique which they have evolved from long evolution and learning cycle