COMPUTER SCIENCE & ENGINEERING

Now a days IoT technologies are emerging technology with wide range of applications. Wireless sensor networks (WSNs) are plays vital role in IoT technologies. Construction of wireless sensor node with low-power radio link and high-speed processors is an interesting contribution for wireless sensor networks and IoT applications. Most of WSNs are furnished with battery source that has limited lifetime. The maximum operations of these networks require more power utility. Nevertheless, improving network efficiency and lifetime is a curtail issue in WSNs. Designing a low powered wireless sensor networks is a major challenges in recent years, it is essential to model its efficiency and power consumption for different applications. This paper describes power consumption model based on LoRa and Zigbee protocols, allows wireless sensor nodes to monitor and measure power consumption in a cyclic sleeping scenario. Experiential results reveals that the designed LoRa wireless sensor nodes have t...

Expansive scale information accumulation by methods for remote sensor system and web of-things innovation postures different difficulties in perspective of the confinements in transmission, calculation, and vitality assets of the related remote gadgets. Com-pressive information gathering in light of packed detecting has been demonstrated an appropriate answer for the issue. Existing plans misuse the spatiotemporal connections among information gathered by a particular detecting methodology. Be that as it may, numerous applications, for example, ecological checking, include gathering heterogeneous information that are inherently corresponded. By this examination, we are trying to propose the use of relationship from different heterogeneous signs while recouping the information from compressive estimations.  

In today’s everlasting technological world, information and data communication create more devices stay connected to the internet. This lead to achieving development for building different software and internet connection very inexpensive this affected privacy and security. Security today became of the most important issue because day-by-day new technologies are put forward for different purposes of study while these come with a lot of vulnerabilities which makes the exploitation of the data. IoT is also such kind technology which is available for exploiting. For preserving information from such type of attacks we use honeypot which serves as a decoy based technology in a network and these are cost effective and works as a deception model which entice attackers with low vulnerabilities and security. Here are how honeypots used to defend IoT devices from being attacked and gather information about the attackers’ device. 

Wireless sensor networks are the sensors which are acclimated to sense the environmental condition like temperature, pressure, sultriness, moisture etc, sensing the environment parameters and sending them to the gateway and retrieving the aggregated data from the gateway to the end user. Power is the major constraint in wireless sensor networks. One must need to reduce the power consumption. Wireless sensor networks have sensor nodes in which each node has a processor, antenna and a battery. The batteries consume power so that we require increasing the lifetime of the battery for that some optimization techniques are required to reduce the power consumption. There are some techniques which are inspired from the lifestyle of animals. In this paper proposing an optimization technique which is inspired by the animal demeanor which reduces the power consumption of the sensor nodes which is particle swarm optimization (PSO) technique. PSO is inspired by the convivial demeanor of birds or...

This paper subsumes the implementation of automation in tracking the electrical consumption data of household systems over the network (WEB). This could sub-sequentially cut down the manual work involved in the process of collecting no: of units consumed from each house, thereby avoiding the manual costs and errors by building an automatic network access. The installation of this system is quite an easy task, which do not need much hardware work. The key elements that make this system are Current sensor and Voltage sensor interfaced to an Arduino board (A General Purpose Micro Controller board) with an Ethernet shield and a WIFI Router for transmission of data wirelessly to the server for storing consumption values into the database. Hosting web pages with the database connectivity will make the administrator generate electricity bill automatically that facilitates user’s to view and pay his electricity bill online.

Clustering is a division of data into groups of similar objects. Representing the data by fewer clusters necessarily loses certain fine details, but achieves simplification. Cluster is nothing but a group. In the view point of data engineering cluster is a group of objects with similar nature. The grouping mechanism is

In the centralized cloud controlled environment, the decision-making and monitoring play crucial role where in the host controller (HC) manages the resources across hosts in data center (DC). HC does virtual machine (VM) and physical hosts management. The VM management includes VM creation, monitoring, and migration. If HC down,the services hosted by various hosts in DC can't be accessed outside the DC. Decentralized VM management avoids centralized failure by considering one of the hosts from DC as HC that helps in maintaining DC in running state. Each host in DC has many VM's with the threshold limit beyond which it can't provide service.To maintain threshold , the host's in DC does VM migration across various hosts. The data in migration is in the form of plaintext, the intruder can analyze packet movement and can control hosts traffic. The incorporation of security mechanism on hosts in DC helps protecting data in migration. This paper discusses an approach for dynamic HC selection, VM selection and secure VM migration over cloud environment.

Hosts in distributed cloud environment configured with Local Resource Monitors (LRM) that runs autonomously, monitors underlying host's resource usage and balances underlying host's resource usage by migrating Virtual Machine (VM) to other hosts. LRM takes decision for VM migration at fixed interval considering own current CPU usage and the other hosts CPU usage. The peer hosts unawares about the decision taken by the other hosts LRM about VS migration. As a result of this, there are chances that the same host selection from multiple hosts during the VS placement. This results into destination host to over utilized or the LRM at destination host initiates the VS migration. Several approaches have been proposed for decentralized VS placement that includes two threshold based VS placement, hypercube based VM placement, Ant Colony based VS placement. These approaches does not considers future behavior of the destination hosts after VS placement. This paper discusses the decentralized peer to peer Virtual Server Placement Approach (DPPVP) that considers host's current as well future CPU utilization for VS placement. The results shows that the proposed system avoids the over utilization of the destination host and host identification by the multiple hosts during VS placement.

We propose a location geometric similarity scoring method that is invariant to rotation, scale, and translation, and can be easily incorporated in mobile visual search and augmented reality systems. We present a fast and efficient geometric re-ranking method that can be incorporated in a feature based image-based retrieval system that utilizes a Vocabulary Tree (VT). We form feature pairs by comparing descriptor classification paths in the VT and calculate geometric similarity score of these pairs. We compare the performance of the location geometric scoring scheme to orientation and scale geometric scoring schemes. We show in our experiments that re-ranking schemes can substantially improve recognition accuracy. We can also reduce the worst case server latency up to 1 sec and still improve the recognition performance.

Epidemiology is the study of spread of diseases among the group of population. If not controlled properly, the epidemic would cause
an enormous number of problems and lead to pandemic situation. Here in this paper we consider the situation of populated areas
where people live in patches. A dynamic cellular automata model for population in patches is being proposed in this paper. This
work not only explores the computing power of cellular automata in modeling the epidemic spread but also provides the pathway
in reduction of computing time when using the dynamic cellular automata model for the patchy population when compared to
the static cellular automata which is used for a nonpatchy homogeneous population.The variation of the model with movement of
population among the patches is also explored which provides an efficient way for evacuation planning and vaccination of infected
areas.

Epidemics is very important area of concern for
most our living being family in the world. Any
epidemic situation when properly not controlled
could lead to a disaster when large amount of
human population is involved. Here we propose
a fundamental model of computation in terms of
non-deterministic finite automata (NFA) for the
Susceptible-Infectives-Recovered (SIR) model.
Through this model we could prove there could
be certain languages which are epidemic regular
since it could be compared with the normal
regular languages for which we can have NFA or
regular grammar. If we could classify how the
epidemic model could behave then we could
better develop strategies that could tackle a
similar epidemic situation in future. This model
has been tested with the data of H1N1 obtained
from CDC USA

The world without a disease is a dream of any human being. The disease spread if not controlled could cause an epidemic situation to spread and lead to pandemic. To control an epidemic we need to understand the nature of its spread and the epidemic spread
model helps us in achieving this. Here we propose an epidemic spread model which considers not only the current infective
population around the population but also the infective population which remain from the previous generations for computing
the next generation infected individuals. A pushdown cellular automata model which is an enhanced version of cellular automata by adding a stack component is being used to model the epidemic spread and the model is validated by the real time data of H1N1 epidemic in Abu Dhabi.

This paper is focused on a cellular automata based computational model for the spread of disease named Leptospirosis using voting rules. Leptospirosis is most commonly found in bovine rats and the humans get infected when they come into contact
with them. The disease spread is modelled in terms of Susceptible-Infective-Recovered-Susceptible (SIRS) model through one of the efficient computational modeling tool–Cellular Automata (CA); and requires strategic change in the rule set of the traditional CA. An idea of voting based rule on the neighborhood environment is studied for modeling the Leptospirosis and compared with real data of such infection in Thailand during the year 2000 and 2001. The simulation of the model is done with real data of Leptospirosis infection in Thailand during 2000 and 2001 and the results yielded from this model were closely in match with the real time data.

Parsing is a technique for processing of sentence. Clinical parser is used for clinical narratives by using medical lexicons. These clinical narratives is in unstructured format so parser is used for converting in to structured format so that it can be readable by anyone. Clinical Parser depends on type of reports as different medical reports is having different format as well as these reports differ from hospital to hospital also. In this paper we are describing about clinical parser for different types of reports by using phrase structured grammar rules. PCFG (probabilistic context free grammar) is used for approximation of tree in which each rule is having probability.

Agriculture plays a very important role in the development of Indian economy. Farmers if aware about their surroundings can contribute widely in the agricultural development. Many improvements and enhancement have been inculcated from past to help the farmers so that optimum utilisation of resources, maintaining the fertility of soil, temperature, humidity , efficient usage of power and irrigation methods, etc can be achieved. This may not only beneficial to the famers but also to the larger section of the rural poor who are directly , indirectly involved in agricultural activities as consumers. This will provide a excellent crop productive environment which facilitates the over all rural development. Beside them, this sector is also facing the crises of lack of man power and lack of water, which adversely affects the production of crops. Use of IoT devices is one of the solution one could find in this type of environment. This paper highlights the comparative study of all the available IoT tools to monitor production of crops. As IoT has already entered the agricultural domain, itshowcased efficient ways to increase and maintain thecropproduction, balanced prices of agricultural tools, herbicides, fertilizers etc. The use of IoT devices for agriculture especially for developing and monitoring crop production hasled to the collaborated environment necessary for the development of the economy as a whole.

The issue of leakage in the irrigation pipeline of an agricultural setup not only contributes to the wastage of water but if the water becomes contaminated then its spread due to leakage may harm the crop and also add to the spread of the disease, if any, in the crop. There are many signal based as well as model based techniques for detection of leakage in the water pipeline. From the study carried out, it is evident that model-based techniques are more suitable for agriculture's irrigation setup. This research paper presents cellular automata-based leakage detection techniques in smart drip irrigation setup for preventing disease to spread in the crop by detecting the leakage, cutting the water supply to that drip pipe and sending SMS to the farmer so that timely action could be taken to treat the leakage area thereby preventing contamination and spread of water to the field preventing the spread of disease to the crop and aiding in water conservation. Moreover, the paper also demonstrates experimental results and discussion of the real time data collected from the soil moisture sensors, flow sensors, rain sensors for three different dates and different time validates the proposed work. Water is a necessary resource for life, health, economic growth and the environment globally. Since water is important to all, it is necessary to ensure its availability and quality [1]. Some of the global factors like climate change [2], population overgrowth and imbalance [3], drought [4] are playing a major role in reducing the existing fresh water resources. India's economy is an agro-based economy [5]. Around 70% of rural population of India depends on agriculture for their livelihood [6]. Income from agriculture contributes to around 17% in GDP [7]. According to researchers around 70% of the available fresh water, mainly is being consumed in agricultural activities [8]. Leaky pipes can cause flooding and water infiltration, which can lead to cause more severe problems in an agricultural setup. Most commonly, water leaks are from cracked or broken water pipes. A number of factors, including erosion and the shifting of the landscape or soil, can result in cracked pipes. Other factors which can contribute to the leakage in pipe can be due to the result of weather exposure, aging of pipelines, physical damage to the pipeline, tree roots, or other sharp instruments. Leaks can be big or small and require some techniques to detect it. The leakage problems should be immediately addressed by the replacement or repair of damaged valves and pipes so that the after effects which may occur due to water pipeline leakage can be reduced to a greater extent [9]. Some of the issues erupting as a result of contamination of water in agriculture due to leaky pipes are water stress on crop [10], pesticide runoff [11], increased erosion [12], increased nutrient levels and eutrophication resulting in algal blooms [13], waterlogging and salinization of soils [14]. The damage to the pipe has a major effect on the water quality and hydraulics of the water delivery system [15]. Broadly, two classifications exist for leakage detection and localization of water pipeline structure in irrigation setup i.e., signal based techniques and model-based techniques. In signal based techniques, observation is used as a manual process which is a time consuming process and required manual intervention and inspection by a person, which is not ideal for a large field [16], acoustic which is a traditional way of identifying leakage and its accuracy is dependent only on the placement of sensor and it is not ideal from smaller leakage [17], infrared which can be used for shorter distance with continuous monitoring [18], fibre optics which gives precise leak detection but it is suitable for shorter distance [19], tracer gas which uses combination of insoluble gases to detect the leakage but they are not suitable for old pipelines as the gas may evade through the gaps of the joints [20], and ground penetrating radar which employs electromagnetic waves to detect and locate leak in the pipeline but they are more suitable for underground pipelines and also the disturbance if any may make this technique inefficient to detect and locate leakage [21]. In model based techniques, deep learning model is employed which uses logic based learning models like CNN and ANN with limitation that higher number of hidden layers are needed for more accurate detection [22], negative pressure wave model with limitation of more false alarm [23], mass

The research paper explains the cellular automata based model that uses pressure variation, soil moisture variation, rain sensor, and GPS sensor to detect and locate plausible leak in a prototype smart drip irrigation pipeline structure. In order to discover that the possible leak is not a False Positive leak and also to obtain accurate location of leakage in the water pipeline structure, cellular automata based algorithm is used along with the Euclidean distance an also the rain sensor and GPS sensors are used for comprehensive and near accurate localization. The whole network comprises mainly of four blocks i.e., hardware and middleware block, real time data collection, storing and analysis block, pipeline leakage localization decision block, and action & communication block. If deployed in IoT based drip irrigation system in India, the farmers with the help of the proposed model will be able to remotely monitor the water pipeline structure for any plausible leaks and reduce the wastage of water and economic loss resulting from such situation.