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Purpose The purpose of this paper is to provide an overview of smart agriculture systems and monitor and identify the technologies which can be used for deriving traditional agriculture system to modern agriculture system. It also provides the reader a broad area to work for the advancement in the field of agriculture and also explains the use of advanced technologies such as spectral imaging, robotics and artificial intelligence (AI) in the field of agriculture. Design/methodology/approach Smart uses of modern technologies were reviewed in the field of agriculture, which helps to monitor stress levels of plants and perform operations according to requirements. Operations can be irrigation, pests spray, monitoring crops, monitoring yield production, etc. Based on the literature review, a smart agriculture system is suggested. The parameters studied were spectral image processing, AI, unmanned aerial vehicle (UAVs) (fixed and rotatory), water or soil moisture, nutrients and pesticides. Findings The use of autonomous vehicles and AI techniques has been suggested through which the agriculture system becomes much more efficient. The world will switch to the smart agriculture system in the upcoming era completely. The authors conclude that autonomous vehicle in the field of science is time-saving and health efficient for both plants and workers in the fields. The suggested system increases the productivity of crops and saves the assets as well. Originality/value This review paper discusses the various contemporary technologies used in the field of agriculture and it will help future researchers to build on this research. This paper reveals that the UAVs along with multispectral, hyperspectral or red, green and blue camera (depends on the need) and AI are more suitable for the advancement of agriculture and increasing yield rate.

Brain Stimulation is now becoming the preferred approach where pharmacological treatment is ineffective in neurological conditions such as Parkinson’s Disease (PD), Tourette Syndrome, Addiction disorder, Depression, and Anxiety. The brain can be stimulated by electrical current, light, and sound energy, invasively or non-invasively. The article comprises of pathophysiology in Parkinson’s, current pharmacological modalities used for the treatment (along with limitations), and deep brain stimulation as the last resort. The article also provides a comprehensive analysis of intelligent Deep Brain Stimulation methods (procedure, architecture, and type) from the studies and research conducted in the last five years. In the end, research gaps and associated challenges are discussed.

Automation in agriculture nowadays is the main focus and area of development for various countries. The population rate of the world is increasing rapidly and will be double in upcoming decades and the need of food is also increasing accordingly. To meet this rapid growth in demand, agriculture automation is the best solution. Traditional strategies employed by farmers are not efficient enough to fulfill the rising demand. Improper use of nutrients, water, fertilizers and pesticides disturbs the agricultural growth and the land remains barren with no fertility. This research paper presents different control strategies used to automate agriculture such as: IoT, aerial imagery, multispectral, hyperspectral, NIR, thermal camera, RGB camera, machine learning, and artificial intelligence techniques. Problems in agriculture like plant diseases, pesticide control, weed management, irrigation and water management can easily be solved by different automated and control techniques mentioned above. Automation by advance control strategies of agricultural methods have verified to increase the crops yield and also the soil fertility become strong. This research paper reviews and observe the work of different researchers to present a brief summary about the trends in smart agriculture and also provides the work flow and revenue of smart agriculture system in figure 15 using technologies verified by researchers in their research papers.

According to findings made during a surveyperformed at malls, consumers have difficultydetermining their best preferences and requirementswhile shopping. Local marketers confront severalobstacles. They don't have access to a platform that mayaid in the expansion and growth of their sales andbusiness. Following this statistic, Shopick was created,which would be beneficial to both customers andsuppliers.Keywords — E-Commerce, Digital Marketing, OnlineShopping, Brands, Trends, Digital Communication, MarketingStrategy, Marketing Budget, Local Business, Advertising, SocialMedia and Geolocation.

In today’s competitive world software organizations are moving towards global software development environment where experts in teams from different geographical locations and different cultures are working on their roles and responsibilities to deliver a quality and cost-effective product. These teams are distributed in nature and work on same set of goals and objectives. They are undertaking their assignments to get multiple advantages like global exposure, new software world to explore, learning environment, etc. This change is having a significant effect on marketing and distribution as well as on the way software products are perceived, designed, developed, tested, and delivered to customers. Software experts in Global Software Development environment are also facing many challenges like as well. Moreover, risk is a big challenge out of other challenges but not many researchers addressed risk related to Time, Budget and Resources. Developing software projects to address business needs and requirements is so exceedingly complex and troublesome that it is common for software projects to overrun budgets and exceed scheduled completion dates. Business managers need the whole development process streamlined and more manageable, with projected cost and timings and for better decision making. The utilization of artificial intelligence techniques to manage risk is helpful when taking care of and assessing unstructured information because of the self-learning and self-healing nature of artificial intelligence-based algorithms. In this paper an Artificial Intelligence based architecture has been proposed that reduces risk by using Time, Budget and Resource constraints that will help decision maker to take decisions and get optimal solutions.

The traditional networks are facing difficulties in managing the services offered by cloud computing, big data, and the Internet of Things as the users have become more dependent on their services. Software-Defined Networking (SDN) has pulled enthusiasm in the integration process of technologies and function as per the user's requirements for both academia and industry, and it has begun to be embraced in actual framework usage. The emergence of SDN has given another idea to empower the focal programmability of the system. Because of the increasing demand and the scarcity of resources, the load balancing issue needs to be addressed efficiently to manage the incoming traffic and resources and to improve network performance. One of the most critical issues is the role of the controller in SDN to balance the load for having a better Quality of Service (QoS). Though there are few survey articles written on load balancing, there is no detail and systematic review conducted in load balancing in SDN. Hence, this paper extends and reviews the discussion with a taxonomy of current emerging load balancing techniques in SDN systematically by categorizing the techniques as conventional and artificial intelligence-based techniques to improve the service quality. The review also includes the study of metrics and parameters which have been used to measure the performance. This review would allow gaining more information on load balancing approaches in SDN and enables the researchers to fill the current research gaps.

The past few years have witnessed the emergence of a novel paradigm called cloud computing. CC aims to provide computation and resources over the internet via dynamic provisioning of services. There are several challenges and issues associated with implementation of CC. This research paper deliberates on one of CC main problems i.e. load balancing (LB). The goal of LB is equilibrating the computation on the cloud servers such that no host is under/ overloaded. Several LB algorithms have been implemented in literature to provide effective administration and satisfying customer requests for appropriate cloud nodes, to improve the overall efficiency of cloud services, and to provide the end user with more satisfaction. An efficient LB algorithm improves efficiency and asset's usage through effectively spreading the workload across the system's different nodes. This review research paper objective is to present critical study of existing techniques of LB, to discuss various LB parameters i.e. throughput, performance, migration time, response time, overhead, resource usage, scalability, fault tolerance, power savings, etc. The research paper also discusses the problems of LB in the CC environment and identifies the need for a novel LB algorithm that employs FT metrics. It has been found that traditional LB algorithms are not good enough and they do not consider FT efficiency metrics for their operation. Hence, the research paper identifies the need for FT efficiency metric in LB algorithms which is one of the main concerns in cloud environments. A novel algorithm that employs FT in LB is therefore proposed.

Ultimate extreme flash floods can be acknowledged as a main reason of high casualties and infrastructure loss in many countries like Pakistan, Malaysia, Philippines, Southern France, India, Bangladesh, China, Nepal, Canada, United States of America and others. Run offs can devastate huge buildings and personal belongings within fraction of seconds. Flash floods usually occurs due to many reasons like higher precipitation velocity, melting of ice debris in ocean, high wave current at sea shore, broken reservoir (dam), Cloud to ground flashes, thunderstorm and hurricane inside the ocean. More than one hundred and twenty thousand casualties resulted due to the flash floods during the 1992 and 2005. According to the literature review deadliest flash floods have been observed in past history. Many approaches have been completed to investigate the flash floods accurately and precisely with less false alarm rate. Disaster management authorities are unable to forecast the natural disasters accurately and precisely like tsunami, flash floods, hurricanes and seismic events due to the poor efficiency of the sensors and transmission of missed information. It has also been observed that during the wireless data transmission of sensors to the controller unit some bits of the data are missed, due to these phenomena data is not transmitted properly or indicate the wrong observations. Several diversified approaches have been made to identify the run offs more accurately and precisely. Generally, the approaches can be classified into two categories a) Engineering Based b) Non-Engineering Based. Engineering techniques based on the construction of the dams and reservoirs to store the excess water which causes severe run offs. Designing of various Artificial Intelligence Based competent algorithms to predict the flash floods vigorously can be considered as non-engineering based approaches. Authors have tried their best to summarize and portray all the successful techniques that can be used for the early prediction of flash floods. Scientists can be benefited by this research paper as this research paper is the detailed capsulization of all the approaches that has been carried out for the robust investigation of flash floods. Extensive literature review has been done to observe the comparative analysis for the investigation of flash floods identification accurately. Literature review has been categorized into following types; 1. Sensory Fusion based 2. Artificial Intelligence Based methods 3. Radar and Satellite based approaches 4. Modeling and Nowcasting. According to the exhaustive literature review it can be concluded that swarm intelligence weights optimization for multi-layer perceptron neural network configuration performed better among all the forecasting approaches and recommended as the future enhancement.

Routing protocols are used to transmit the packets from the source to the destination node in mobile ad hoc networks. The intruders seek chance to pierce into the network and becomes a cause of malfunctioning in the network. These protocols are always prone to attacks. During the phases of routing in different types of protocols, each of the attack finds a way to degrade the performance of the routing protocols. The reactive routing protocols DSR and AODV have lot of similar features and so are considered in this study. In order to transmit the packets safely, a secured approach using triple factor has been proposed. This triple factor computes the trust by using the direct information then verifies the reputation by collecting the information from the neighbouring nodes called distributed factor and uses cryptographic algorithm to ensure security. And to ensure that there are routes available to perform the routing process, the reasons for such attacks are studied so as to re-integrate back the nodes in to the network, once it has repented for being malicious before. The availability of routes increases the throughput.

Artificial intelligence (AI) is one of the emerging technologies. In recent decades, artificial intelligence (AI) has gained widespread acceptance in a variety of fields, including virtual support, healthcare, and security. Human-Computer Interaction (HCI) is a field that has been combining AI and human-computer engagement over the past several years in order to create an interactive intelligent system for user interaction. AI, in conjunction with HCI, is being used in a variety of fields by employing various algorithms and employing HCI to provide transparency to the user, allowing them to trust the machine. The comprehensive examination of both the areas of AI and HCI, as well as their subfields, has been explored in this work. The main goal of this article was to discover a point of intersection between the two fields. The understanding of Explainable Artificial Intelligence (XAI), which is a linking point of HCI and XAI, was gained through a literature review conducted in this research. The literature survey encompassed themes identified in the literature (such as XAI and its areas, major XAI aims, and XAI problems and challenges). The study’s other major focus was on the use of AI, HCI, and XAI in healthcare. The poll also addressed the shortcomings in XAI in healthcare, as well as the field’s future potential. As a result, the literature indicates that XAI in healthcare is still a novel subject that has to be explored more in the future.

In this paper, a novel wideband circularly polarized multiple-input multiple-output (MIMO) dielectric resonator antenna (DRA) has been proposed for worldwide interoperability for microwave access (WiMAX) applications. The mutual coupling (MC) between closely placed DRA units at 0.5λ has been significantly reduced by using a new hybrid technique. The exclusive features of the proposed MIMO antenna include wide impedance matching bandwidth (BW), broadband circular polarization (CP), and suppressed MC between the radiating elements. The first step of hybrid technique is the employment of parasitic patch at an optimized distance beside the conformal metal strip of the two identical rectangular DRAs in order to generate CP wave along with a wide impedance matching BW over the same frequency range. In the final step, the MC is suppressed significantly along with the broadband CP by placing the DRAs diagonally at an optimized position. The proposed MIMO antenna is the hybrid of the parasitic patch and the diagonal position of radiating elements. The CP BW offered by the proposed antenna is ~20.82% (3.58-4.40 GHz) in conjunction with an impedance-matching BW of ~38.51% (3.50-4.95 GHz). Moreover, MC less than -28 dB is achieved over the entire band and -26 dB at 3.89 GHz (minimum of the AR) through the hybrid technique. The prototype of the proposed antenna geometry is fabricated and measured. A good agreement has been attained between the simulated and measured results.

A wideband circularly polarized rectangular dielectric resonator antenna (DRA) fed by single feeding mechanism has been studied theoretically and experimentally. The study has been carried out to find out the effect on different antenna parameters when a parasitic strip is attached to the wall beside the conformal metallic feed. The DRA is excited by an E-shaped metal strip. The novel feed produces a narrow impedance matching |S11

It is succinct as per the topic that it will focus on IoT-based security issues. The topic is emerging so contemplation is required to bridge scanty in this field. This study will focus on a rigorous literature review which will provide us scrupulous path to satisfy the industry need. In curtail IoT is not just about interconnecting embedded devices or gadgets to the Internet, however, it is also fast and continuously growing to improve the ease or satisfaction of life. The motive of IoT services is to connect the entire globe through sensors. This study reviews the IoT methodologies in the light of qualitative research. The data analysis and synthesis focus over the last three years (2018 to 2020) which are based on the PRISMA block diagram for understanding. The review identifies the IoT privacy and security issues from a different perspective and also finds out which security issue is mostly discussed in the last few years which elaborated as a basis for further research. After a review of this paper, we can easily understand the different problem faces of IoT devices with the help of comparative analysis using summary tables and graphical representation of IoT in the context of the privacy and security challenges and issues face of IoT devices. After vigorous contemplation, it is clear that in future most of the paper will discuss data security and privacy, confidentiality, and authenticity.

In Cloud computing environment the resources are managed dynamically based on the need and demand for resources for a particular task. With a lot of challenges to be addressed our concern is Load balancing where load balancing is done for optimal usage of resources and reduces the cost associated with it as we use pay-as-you-go policy. The task scheduling is done by the cloud service provider using preemption and non-preemption based on the requirements in a virtualized scenario which has been focused here. In this paper, various task scheduling algorithms are studied to present the dynamic allocation of resources under each category and the ways each of this scheduling algorithm adapts to handle the load and have high-performance computing

A circularly polarized rectangular dielectric resonator antenna (DRA) has been designed (3.7–4.2 GHz) for WiMAX, satellite, and sub-6 GHz 5G NR band communications. A new T-shaped monopole has been used to excite the rectangular DRA. Using proposed conformal metal strip, the higher-order degenerate modes TE δ 13 x and TE 1 δ 3 y have been excited to achieve circular polarization (CP) with improved gain. Further, the bandwidths enhancement has been achieved by placing a parasitic patch of optimized height and width at a specific distance from T-shaped strip on DRA surface to cover the desired frequency band. A signaficant enhancement of ~ 73% in the impedance-matching bandwidth and ~ 75.5% in axial ratio (AR) bandwidth has been achieved. The | S 11 | ≤ 10 dB over a wide bandwidth of ~ 17.3% has been offered by the antenna. A broad axial ratio bandwidth of ~ 17.2% along with a useful gain of ~ 6.32 dBic has been provided by the antenna. The antenna designing and optimization has been carried out using CST® Microwave Studio. A reasonable agreement between simulated and measured results has been observed.

RFID (Radio Frequency Identification) is the fastest growing technology, as many IoT devices are communicating via RFID technology. During the interaction among RFID reader and tag, collision happens in different ways like tag-to-tag, reader-to-reader and reader-to-tag collisions. Several anti-collision techniques are presented to resolve the collision issue. The RFID reader is like a physical sensor; thus, this study shows how the context-aware process is used in the reader and tag interaction. Furthermore, the authors have discussed the context of RFID anti-collision protocol by analyzing how a reader reads a tag and detects collision from a context-aware perspective. This study examines the method of working of anti-collision techniques from a context-aware perspective. The study gives a brief overview of how an anti-collision technique is working in RFID reader and tag communication. The core focus of this study is to compare anti-collision techniques and examine from a context-aware perspective. In this paper, RFID reader and tag communication is mapped with a context-aware cycle. By examining anti-collision techniques as an outcome, efforts have been made in this paper to determine which anti-collision technique is working better from a context-aware perspective. As per our findings, the discontinuous collision bit mapping algorithm (DCCMA) is a better approach as compared to other anti-collision techniques. Through this paper, we have found out that (DCCMA) anti-collision technique is better from a context-aware perspective.

Global software development is an example of the modern age. Team members split geographically, working in different time zones, communicate simultaneously and exchange information regardless of physical boundaries and time difference. Different organizations are distributing their software development processes on national and continental lines. Team members work across space, time and organizational boundaries with links strengthened by webs of communication technologies. In order to obtain robust solutions at reasonable costs in different software development processes like software reliability, quality, maintenance, effort and different project management activities, different researchers used soft computing techniques. In this paper several existing research articles are reviewed that deal with the applications of soft computing in software development areas and provides future research directions.

In the real time processing, a new emerging technology where the need of connecting smart devices with cloud through Internet has raised. IoT devices processed information is to be stored and accessed anywhere needed with a support of powerful computing performance, efficient storage infrastructure for heterogeneous systems and software which configures and controls these different devices. A lot of challenges to be addressed are listed with this new emerging technology as it needs to be compatible with the upcoming 5G wireless devices too. In this paper, the benefits and challenges of this innovative paradigm along with the areas open to do research are shown., ICETAS IEEE Proceedings 2017

Cloud computing and the services offered by cloud computing in the field of Information and Communication Technology has impacted the enterprises and is stimulating at a more prominent pace in the recent years. Various studies have been conducted in the field to meet the client’s requirements and raise the quality of services offered. Based on the client’s requests and integrating it with load balancing as one of the challenges of cloud computing to be addressed the cloud services are ranked. In order to offer better services to the clients and to maintain the trust, load balancing as one of the criteria in real time scheduling is adopted. In order to attain ranking, different services are required to be invoked in the cloud, the requirement factors and the ranking criteria for each factor has been considered to rank them using entropy analysis of Shannon Furthermore, a framework has been proposed to rank them based on the weights attained by the requirements and the ranking criteria.

Global software development is increasingly used in organizations where specialized skills are required to address specialized software development and support. The Global software development industry is such business that has had a huge impact over the last several years, demanding expert resources and their timely availability whenever and wherever needed. This dependence on software engineering has led to the transformation of the way the softwares are being developed today. Project team members from different geographical locations and cultures are involved in software development and getting many benefits include cost advantage, time, risk, productivity and 24/7 development. Communication and collaboration are the key technologies used in Global software development. These tools have their inherent problems and gray areas on which further research is required. These technologies must ensure the availability of sufficient resources, Project management needs to monitor project progress and status reports, planned milestones that must be understood and agreed among all team members and a refined high-performance process of Global Software development without unnecessary project activities that creates delays in the project. In this paper several communication barriers have been addressed that lead to project failure. The need to use faster, cheaper and cost effective means of communication tools has exerted a lot of pressure on software professionals to cater to the demand of the global world.

Intense and severe torrents, tornadoes and thunderstorm causes numerous casualties in fraction of second and extreme devastation of infrastructure in many countries. Flash floods are considered one of the most hazardous natural disasters. Several approaches have been made for an authentic and robust early warning system to forecast the flash floods vigorously. An intelligent and vibrant model for the recognition of floods includes the estimation of water level, Global Positioning System-Precipitable Water Vapor (GPS PWV), precipitation velocity, wind speed, direction, upstream levels of river, soil moisture, oceanic bottom pressure and color of the water with accurate and reliable cognition algorithms. UGS (unattended ground sensors) and langrangian micro transducers are deployed on the ground and spread on the sea surface respectively to investigate the hydrological and meteorological differences on real time basis. By the utilization of fuzzy logic, Kalman filtering, Adaptive neuro fuzzy interference system (ANFIS), Particle Swarm Optimization (PSO) and Neural network autoregressive model with exogenous input (NNARX) based structure. Reduction of complexities in data collection, high false alarm rates, communication issues, low WSN battery backup and all related hindrances have been the focal point of this research paper.

Developing Software through a globally distributed team is a modern trend, which is not only cost effective but also yields best project results mitigating risk and increasing return on investment. This is easily achieved by ensuring through put in production is maintained at all times irrespective of the clock time and geographical boundaries. This shift of phenomenon is happening across the board as more and more companies use this as a strategic tool. Modern day technology makes this all possible, without compromising quality, coding practices and project management techniques. In this paper we have researched several papers (2008 to 2018) and understood the data for soft computing to provide a strong basis for future directions

The collection and dissemination of increasing quantities of information representing multiple digital media objects are promising, combined with a number of technical advances in ICT. Even though the information is maintained and distributed by different owners, systems, formats and locations, their contents might tell the same story, share the same space-time extension, and they might be closely related to each other. Previous efforts in information retrieval and integration have been limited to classical keyword-based and content-based indexing and querying for multiple media documents. Furthermore, the concept-based approach, which is becoming a very popular method, still focuses on specific single media documents. Thus, a concept-based system architecture that allows access to information in multiple format - text, image and graphic, audio, video and spatial information - within heterogeneous sources is presented in this paper. This architecture conforms to the Service Oriented Architecture standards and is designed with the use of ontologies in order to comprehend the semantic matchmaking between users' queries and multi-format information through metadata. The basis of the ontology model is already in place, but the architecture still undergoes its incremental progress as a research prototype within the disaster management domain.

This research work is focusing on the location estimation by using interpolated distance calculation and its error in wireless nodes based on different clutters/terrains. This research is based on our previous findings in which we divided the clutter/terrain into thirteen different groups. As radio waves behave differently in different terrains therefore we recorded data points in all different terrains. C# program was used with WiFi (IEEE 802.11) prototype to record the behavioral changes in radio signals because of atmospheric attenuation. We took readings in all different clutters at a regular interval of 10 meters (from 10m to 150m). In current research, we are using linear interpolation to calculate the distances other than regular interval with minimal error rate. First, we calculate actual distance based on receive radio signals at random and then compare it with our interpolated distance and calculate the error. We take a sample size of four in each terrain and divide the interpolated data in six zones for accuracy. This comparison table helps to estimate the location of wireless node in different terrains/clutters with the error rate of as minimum as 0.5 meter.

The main objective of this research is to apply statistical location estimation techniques in cellular networks in order to calculate the precise location of the mobile node. Current research is focusing on the combination of Kalman filter and the Bayesian decision theory based location estimation. In this research basic four steps of Kalman filter are followed which are Estimation, Filtering, Prediction and Fusion. Estimation is done by using Receive Signal Strength (RSS), Available Signal Strength (ASS) and the Angle of Arrival (AOA). Filtering is done by calculating the average location and variation in values of location. Prediction is done by using the Bayesian decision theory. Fusion is done by combining the variances calculated in filtering step. Finally by combining the prediction and fusion results PCLEA (Predicted and Corrected Location Estimation Algorithm) is established. Timestamp is used for recursive step in kalman filter. The aim of this research is to minimize the dependence on the satellite based location estimation and increase its accuracy, efficiency and reliability.