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Dr. Deepak Prashar
Lovely Professional University, Jalandhar, Punjab, India

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0 Wireless Sensor Network
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Short Biography

Dr. Deepak Prashar received a B.Tech in Computer Science and Engineering from Punjab Technical University, Punjab, India in 2007 and an M.Tech in Computer Science and Engineering from PEC University Of Technology, Chandigarh, India in 2009. Presently, he is working as an Associate Professor and Head of Department of Networking & Security in the Computer Science Department at Lovely Professional University, Punjab, India since 2009. He has published more than 50 research papers in reputed national and international conferences and journals, including SCOPUS and SCIE indexed journals.

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Journal article
Published: 09 August 2021 in Sustainability
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Conventional crop insurance systems are complex and often not economically feasible. Farmers are often reluctant to be covered for their crops due to lack of trust in insurance firms and the fear of delayed or non-payment of claims. In this paper, a blockchain based crop insurance solution is suggested. The solution suggested in this paper is an affordable, efficient, low cost crop insurance solution which will ensure many farmers are insured and benefiting from timely crop insurance. Currently the cost of administering insurance is an essential barrier to accessing this facility. With the proper use of blockchain based on ethereum this expense can be reduced dramatically. We have conducted various tests on platforms such as Google Cloud and found that the least throughput is 165 transactions. Upon analysis we have found that the time taken by the block formation is directly proportional to the timing of processing. The end-to-end average latency of the system was achieved as 31.2 s, which was quite effective for the infrastructure what we are using. Upon conducting acceptance testing, we found that the system suggested in the paper is effective and we are planning to release the application on open source platforms for future improvements.

ACS Style

Nishant Jha; Deepak Prashar; Osamah Ibrahim Khalaf; Youseef Alotaibi; Abdulmajeed Alsufyani; Saleh Alghamdi. Blockchain Based Crop Insurance: A Decentralized Insurance System for Modernization of Indian Farmers. Sustainability 2021, 13, 8921 .

AMA Style

Nishant Jha, Deepak Prashar, Osamah Ibrahim Khalaf, Youseef Alotaibi, Abdulmajeed Alsufyani, Saleh Alghamdi. Blockchain Based Crop Insurance: A Decentralized Insurance System for Modernization of Indian Farmers. Sustainability. 2021; 13 (16):8921.

Chicago/Turabian Style

Nishant Jha; Deepak Prashar; Osamah Ibrahim Khalaf; Youseef Alotaibi; Abdulmajeed Alsufyani; Saleh Alghamdi. 2021. "Blockchain Based Crop Insurance: A Decentralized Insurance System for Modernization of Indian Farmers." Sustainability 13, no. 16: 8921.

Research article
Published: 20 July 2021 in Journal of Healthcare Engineering
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Early diagnosis of pandemic diseases such as COVID-19 can prove beneficial in dealing with difficult situations and helping radiologists and other experts manage staffing more effectively. The application of deep learning techniques for genetics, microscopy, and drug discovery has created a global impact. It can enhance and speed up the process of medical research and development of vaccines, which is required for pandemics such as COVID-19. However, current drugs such as remdesivir and clinical trials of other chemical compounds have not shown many impressive results. Therefore, it can take more time to provide effective treatment or drugs. In this paper, a deep learning approach based on logistic regression, SVM, Random Forest, and QSAR modeling is suggested. QSAR modeling is done to find the drug targets with protein interaction along with the calculation of binding affinities. Then deep learning models were used for training the molecular descriptor dataset for the robust discovery of drugs and feature extraction for combating COVID-19. Results have shown more significant binding affinities (greater than −18) for many molecules that can be used to block the multiplication of SARS-CoV-2, responsible for COVID-19.

ACS Style

Nishant Jha; Deepak Prashar; Mamoon Rashid; Mohammad Shafiq; Razaullah Khan; Catalin I. Pruncu; Shams Tabrez Siddiqui; M. Saravana Kumar. Deep Learning Approach for Discovery of In Silico Drugs for Combating COVID-19. Journal of Healthcare Engineering 2021, 2021, 1 -13.

AMA Style

Nishant Jha, Deepak Prashar, Mamoon Rashid, Mohammad Shafiq, Razaullah Khan, Catalin I. Pruncu, Shams Tabrez Siddiqui, M. Saravana Kumar. Deep Learning Approach for Discovery of In Silico Drugs for Combating COVID-19. Journal of Healthcare Engineering. 2021; 2021 ():1-13.

Chicago/Turabian Style

Nishant Jha; Deepak Prashar; Mamoon Rashid; Mohammad Shafiq; Razaullah Khan; Catalin I. Pruncu; Shams Tabrez Siddiqui; M. Saravana Kumar. 2021. "Deep Learning Approach for Discovery of In Silico Drugs for Combating COVID-19." Journal of Healthcare Engineering 2021, no. : 1-13.

Journal article
Published: 14 April 2021 in Sensors
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Long-range radio (LoRa) communication is a widespread communication protocol that offers long range transmission and low data rates with minimum power consumption. In the context of solid waste management, only a low amount of data needs to be sent to the remote server. With this advantage, we proposed architecture for designing and developing a customized sensor node and gateway based on LoRa technology for realizing the filling level of the bins with minimal energy consumption. We evaluated the energy consumption of the proposed architecture by simulating it on the Framework for LoRa (FLoRa) simulation by varying distinct fundamental parameters of LoRa communication. This paper also provides the distinct evaluation metrics of the the long-range data rate, time on-air (ToA), LoRa sensitivity, link budget, and battery life of sensor node. Finally, the paper concludes with a real-time experimental setup, where we can receive the sensor data on the cloud server with a customized sensor node and gateway.

ACS Style

Shaik Akram; Rajesh Singh; Mohammed AlZain; Anita Gehlot; Mamoon Rashid; Osama Faragallah; Walid El-Shafai; Deepak Prashar. Performance Analysis of IoT and Long-Range Radio-Based Sensor Node and Gateway Architecture for Solid Waste Management. Sensors 2021, 21, 2774 .

AMA Style

Shaik Akram, Rajesh Singh, Mohammed AlZain, Anita Gehlot, Mamoon Rashid, Osama Faragallah, Walid El-Shafai, Deepak Prashar. Performance Analysis of IoT and Long-Range Radio-Based Sensor Node and Gateway Architecture for Solid Waste Management. Sensors. 2021; 21 (8):2774.

Chicago/Turabian Style

Shaik Akram; Rajesh Singh; Mohammed AlZain; Anita Gehlot; Mamoon Rashid; Osama Faragallah; Walid El-Shafai; Deepak Prashar. 2021. "Performance Analysis of IoT and Long-Range Radio-Based Sensor Node and Gateway Architecture for Solid Waste Management." Sensors 21, no. 8: 2774.

Chapter
Published: 11 April 2021 in Studies in Computational Intelligence
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Process Automation has the potential to bring great benefits for businesses and organizations especially in the financial services industry where businesses are information-intensive and experience rich data flows. This was achieved mainly via Robotic Process Automation (RPA), but the increased complexity of the Machine Learning (ML) algorithms increased the possibility of integrating classic RPA with Artificial Intelligence (AI), leading to Robotics 2.0. However, the transition from RPA to Robotics 2.0 embeds a number of challenges. To ensure that the advantages of the modern technologies can be harnessed, these issues need to be tackled. By integrating RPA with cognitive technology such as machine learning, speech recognition, and natural language processing, businesses can automate higher-order tasks with AI assisting that human perceptual and judgment skills were needed in the past. The purpose of this chapter is to identify the set of challenges the companies will face, as well as provide guidance on what preparations to be made before Robotics 2.0 can be implemented in full scale. This also provides the insights about the new intelligent automation approach based on AI integration with RPA in intelligent transportation system.

ACS Style

Nishant Jha; Deepak Prashar; Amandeep Nagpal. Combining Artificial Intelligence with Robotic Process Automation—An Intelligent Automation Approach. Studies in Computational Intelligence 2021, 245 -264.

AMA Style

Nishant Jha, Deepak Prashar, Amandeep Nagpal. Combining Artificial Intelligence with Robotic Process Automation—An Intelligent Automation Approach. Studies in Computational Intelligence. 2021; ():245-264.

Chicago/Turabian Style

Nishant Jha; Deepak Prashar; Amandeep Nagpal. 2021. "Combining Artificial Intelligence with Robotic Process Automation—An Intelligent Automation Approach." Studies in Computational Intelligence , no. : 245-264.

Journal article
Published: 18 January 2021 in Mathematics
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There is an increasing concentration in the influences of nonconventional power sources on power system process and management, as the application of these sources upsurges worldwide. Renewable energy technologies are one of the best technologies for generating electrical power with zero fuel cost, a clean environment, and are available almost throughout the year. Some of the widespread renewable energy sources are tidal energy, geothermal energy, wind energy, and solar energy. Among many renewable energy sources, wind and solar energy sources are more popular because they are easy to install and operate. Due to their high flexibility, wind and solar power generation units are easily integrated with conventional power generation systems. Traditional generating units primarily use synchronous generators that enable them to ensure the process during significant transient errors. If massive wind generation is faltered due to error, it may harm the power system’s operation and lead to the load frequency control issue. This work proposes binary moth flame optimizer (MFO) variants to mitigate the frequency constraint issue. Two different binary variants are implemented for improving the performance of MFO for discrete optimization problems. The proposed model was evaluated and compared with existing algorithms in terms of standard testing benchmarks and showed improved results in terms of average and standard deviation.

ACS Style

Krishan Arora; Ashok Kumar; Vikram Kumar Kamboj; Deepak Prashar; Bhanu Shrestha; Gyanendra Prasad Joshi. Impact of Renewable Energy Sources into Multi Area Multi-Source Load Frequency Control of Interrelated Power System. Mathematics 2021, 9, 186 .

AMA Style

Krishan Arora, Ashok Kumar, Vikram Kumar Kamboj, Deepak Prashar, Bhanu Shrestha, Gyanendra Prasad Joshi. Impact of Renewable Energy Sources into Multi Area Multi-Source Load Frequency Control of Interrelated Power System. Mathematics. 2021; 9 (2):186.

Chicago/Turabian Style

Krishan Arora; Ashok Kumar; Vikram Kumar Kamboj; Deepak Prashar; Bhanu Shrestha; Gyanendra Prasad Joshi. 2021. "Impact of Renewable Energy Sources into Multi Area Multi-Source Load Frequency Control of Interrelated Power System." Mathematics 9, no. 2: 186.

Review
Published: 12 January 2021 in Algorithms for Intelligent Systems
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Over a couple of years, localization has become one of the most prominent tasks in wireless sensor networks (WSNs). Location estimation is one of the major requirements that lead to the emergence of various localization techniques. In addition to the position estimation, security is also one of the prime concerns in the localization process as we the presence of attackers in the network cannot be eliminated. There are various security requirements that need to be fulfilled by the algorithms if we need to make them secure. The previous research lacks the requirements for the design of algorithms that lead to the need of distributed range-free approach as compared to range-based algorithms on account of the use of GPS makes the system more massive and expensive irrespective of accuracy. So, it makes a challenge for researchers to design some range-free approaches. But integrating security aspects in those algorithms is also very challenging and important task. Moreover, the security of multimedia applications is also very important pertaining to the localization. This chapter presents the overview of the localization process in detail along with the issues pertaining to the localization process. Moreover, it covers the need of secure localization to make the process more robust.

ACS Style

Deepak Prashar; Nishant Jha. Review of Secure Distributed Range-Free Hop-Based Localization Algorithms in the Wireless Sensor Networks. Algorithms for Intelligent Systems 2021, 283 -302.

AMA Style

Deepak Prashar, Nishant Jha. Review of Secure Distributed Range-Free Hop-Based Localization Algorithms in the Wireless Sensor Networks. Algorithms for Intelligent Systems. 2021; ():283-302.

Chicago/Turabian Style

Deepak Prashar; Nishant Jha. 2021. "Review of Secure Distributed Range-Free Hop-Based Localization Algorithms in the Wireless Sensor Networks." Algorithms for Intelligent Systems , no. : 283-302.

Journal article
Published: 03 December 2020 in IEEE Access
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Disease diagnosis is the identification of an health issue, disease, disorder, or other condition that a person may have. Disease diagnoses could be sometimes very easy tasks, while others may be a bit trickier. There are large data sets available; however, there is a limitation of tools that can accurately determine the patterns and make predictions. The traditional methods which are used to diagnose a disease are manual and error-prone. Usage of Artificial Intelligence (AI) predictive techniques enables auto diagnosis and reduces detection errors compared to exclusive human expertise. In this paper, we have reviewed the current literature for the last 10 years, from January 2009 to December 2019. The study considered eight most frequently used databases, in which a total of 105 articles were found. A detailed analysis of those articles was conducted in order to classify most used AI techniques for medical diagnostic systems. We further discuss various diseases along with corresponding techniques of AI, including Fuzzy Logic, Machine Learning, and Deep Learning. This research paper aims to reveal some important insights into current and previous different AI techniques in the medical field used in today’s medical research, particularly in heart disease prediction, brain disease, prostate, liver disease, and kidney disease. Finally, the paper also provides some avenues for future research on AI-based diagnostics systems based on a set of open problems and challenges.

ACS Style

Simarjeet Kaur; Jimmy Singla; Lewis Nkenyereye; Sudan Jha; Deepak Prashar; Gyanendra Prasad Joshi; Shaker El-Sappagh; Saiful Islam. Medical Diagnostic Systems Using Artificial Intelligence (AI) Algorithms: Principles and Perspectives. IEEE Access 2020, 8, 228049 -228069.

AMA Style

Simarjeet Kaur, Jimmy Singla, Lewis Nkenyereye, Sudan Jha, Deepak Prashar, Gyanendra Prasad Joshi, Shaker El-Sappagh, Saiful Islam. Medical Diagnostic Systems Using Artificial Intelligence (AI) Algorithms: Principles and Perspectives. IEEE Access. 2020; 8 (99):228049-228069.

Chicago/Turabian Style

Simarjeet Kaur; Jimmy Singla; Lewis Nkenyereye; Sudan Jha; Deepak Prashar; Gyanendra Prasad Joshi; Shaker El-Sappagh; Saiful Islam. 2020. "Medical Diagnostic Systems Using Artificial Intelligence (AI) Algorithms: Principles and Perspectives." IEEE Access 8, no. 99: 228049-228069.

Journal article
Published: 16 June 2020 in Mathematics
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In the recent era, the need for modern smart grid system leads to the selection of optimized analysis and planning for power generation and management. Renewable sources like wind energy play a vital role to support the modern smart grid system. However, it requires a proper commitment for scheduling of generating units, which needs proper load frequency control and unit commitment problem. In this research area, a novel methodology has been suggested, named Harris hawks optimizer (HHO), to solve the frequency constraint issues. The suggested algorithm was tested and examined for several regular benchmark functions like unimodal, multi-modal, and fixed dimension to solve the numerical optimization problem. The comparison was carried out for various existing models and simulation results demonstrate that the projected algorithm illustrates better results towards load frequency control problem of smart grid arrangement as compared with existing optimization models.

ACS Style

Krishan Arora; Ashok Kumar; Vikram Kumar Kamboj; Deepak Prashar; Sudan Jha; Bhanu Shrestha; Gyanendra Prasad Joshi. Optimization Methodologies and Testing on Standard Benchmark Functions of Load Frequency Control for Interconnected Multi Area Power System in Smart Grids. Mathematics 2020, 8, 980 .

AMA Style

Krishan Arora, Ashok Kumar, Vikram Kumar Kamboj, Deepak Prashar, Sudan Jha, Bhanu Shrestha, Gyanendra Prasad Joshi. Optimization Methodologies and Testing on Standard Benchmark Functions of Load Frequency Control for Interconnected Multi Area Power System in Smart Grids. Mathematics. 2020; 8 (6):980.

Chicago/Turabian Style

Krishan Arora; Ashok Kumar; Vikram Kumar Kamboj; Deepak Prashar; Sudan Jha; Bhanu Shrestha; Gyanendra Prasad Joshi. 2020. "Optimization Methodologies and Testing on Standard Benchmark Functions of Load Frequency Control for Interconnected Multi Area Power System in Smart Grids." Mathematics 8, no. 6: 980.

Journal article
Published: 10 June 2020 in Sensors
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The Internet of things (IoT), the Internet of vehicles, and blockchain technology have become very popular these days because of their versatility. Road traffic, which is increasing day by day, is causing more and more deaths worldwide. The world needs a product that would reduce the number of road accidents. This paper suggests combining IoT and blockchain technology to mitigate road hazards. The new intelligent transportation system technologies and the subsequent emergence of 5G technologies will be a blessing, delivering the necessary speed to ensure both safety and quality of service (QoS). Hashgraph technology, a distributed ledger technology is used to create communication networks between the different vehicles and other relevant parameters. Scheduling the requests according to the priorities for ensuring better QoS quotient can be effectively done using hashgraph. We demonstrated how the hashgraph outstrips other equivalents platforms. The proposed model was simulated using OMNeT++ with proper design and network description files. A hardware implementation of the proposed model was also done. Messages were transferred between the vehicles and prioritized using a hashgraph. This paper proposes an effective model in reducing the accidents in terms of parameters like speed, security, stability, and fairness.

ACS Style

Deepak Prashar; Nishant Jha; Sudan Jha; Gyanendra Joshi; Changho Seo. Integrating IoT and Blockchain for Ensuring Road Safety: An Unconventional Approach. Sensors 2020, 20, 3296 .

AMA Style

Deepak Prashar, Nishant Jha, Sudan Jha, Gyanendra Joshi, Changho Seo. Integrating IoT and Blockchain for Ensuring Road Safety: An Unconventional Approach. Sensors. 2020; 20 (11):3296.

Chicago/Turabian Style

Deepak Prashar; Nishant Jha; Sudan Jha; Gyanendra Joshi; Changho Seo. 2020. "Integrating IoT and Blockchain for Ensuring Road Safety: An Unconventional Approach." Sensors 20, no. 11: 3296.

Journal article
Published: 17 May 2020 in Applied Sciences
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Renal cancer is a serious and common type of cancer affecting old ages. The growth of such type of cancer can be stopped by detecting it before it reaches advanced or end-stage. Hence, renal cancer must be identified and diagnosed in the initial stages. In this research paper, an intelligent medical diagnostic system to diagnose renal cancer is developed by using fuzzy and neuro-fuzzy techniques. Essentially, for a fuzzy inference system, two layers are used. The first layer gives the output about whether the patient is having renal cancer or not. Similarly, the second layer detects the current stage of suffering patients. While in the development of a medical diagnostic system by using a neuro-fuzzy technique, the Gaussian membership functions are used for all the input variables considered for the diagnosis. In this paper, the comparison between the performance of developed systems has been done by taking some suitable parameters. The results obtained from this comparison study show that the intelligent medical system developed by using a neuro-fuzzy model gives the more precise and accurate results than existing systems.

ACS Style

Nikita Jindal; Jimmy Singla; Balwinder Kaur; Harsh Sadawarti; Deepak Prashar; Sudan Jha; Gyanendra Prasad Joshi; Changho Seo. Fuzzy Logic Systems for Diagnosis of Renal Cancer. Applied Sciences 2020, 10, 3464 .

AMA Style

Nikita Jindal, Jimmy Singla, Balwinder Kaur, Harsh Sadawarti, Deepak Prashar, Sudan Jha, Gyanendra Prasad Joshi, Changho Seo. Fuzzy Logic Systems for Diagnosis of Renal Cancer. Applied Sciences. 2020; 10 (10):3464.

Chicago/Turabian Style

Nikita Jindal; Jimmy Singla; Balwinder Kaur; Harsh Sadawarti; Deepak Prashar; Sudan Jha; Gyanendra Prasad Joshi; Changho Seo. 2020. "Fuzzy Logic Systems for Diagnosis of Renal Cancer." Applied Sciences 10, no. 10: 3464.

Journal article
Published: 24 April 2020 in Sustainability
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The globalization of the food supply chain industry has significantly emerged today. Due to this, farm-to-fork food safety and quality certification have become very important. Increasing threats to food security and contamination have led to the enormous need for a revolutionary traceability system, an important mechanism for quality control that ensures sufficient food supply chain product safety. In this work, we proposed a blockchain-based solution that removes the need for a secure centralized structure, intermediaries, and exchanges of information, optimizes performance, and complies with a strong level of safety and integrity. Our approach completely relies on the use of smart contracts to monitor and manage all communications and transactions within the supply chain network among all of the stakeholders. Our approach verifies all of the transactions, which are recorded and stored in a centralized interplanetary file system database. It allows a secure and cost-effective supply chain system for the stakeholders. Thus, our proposed model gives a transparent, accurate, and traceable supply chain system. The proposed solution shows a throughput of 161 transactions per second with a convergence time of 4.82 s, and was found effective in the traceability of the agricultural products.

ACS Style

Deepak Prashar; Nishant Jha; Sudan Jha; Yongju Lee; Gyanendra Prasad Joshi. Blockchain-Based Traceability and Visibility for Agricultural Products: A Decentralized Way of Ensuring Food Safety in India. Sustainability 2020, 12, 3497 .

AMA Style

Deepak Prashar, Nishant Jha, Sudan Jha, Yongju Lee, Gyanendra Prasad Joshi. Blockchain-Based Traceability and Visibility for Agricultural Products: A Decentralized Way of Ensuring Food Safety in India. Sustainability. 2020; 12 (8):3497.

Chicago/Turabian Style

Deepak Prashar; Nishant Jha; Sudan Jha; Yongju Lee; Gyanendra Prasad Joshi. 2020. "Blockchain-Based Traceability and Visibility for Agricultural Products: A Decentralized Way of Ensuring Food Safety in India." Sustainability 12, no. 8: 3497.

Article
Published: 13 December 2019 in Wireless Personal Communications
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Nature inspired computing has become one of the necessities of real time application-based methods. While considering the localization aspects of the wireless sensor network, the significance of optimization techniques plays a crucial role in the precise and accurate position estimation of the sensor node. This article provides an optimized form of the error correction metric-based hop localization algorithm based on swarm intelligence approach covering adaptive particle swarm optimization. From the experimental evaluation, it is inferred that under the effect of variable node number, anchor number and the range, the proposed optimized algorithm performs better than alternative algorithms having identical characteristics. From the implementation and performance analysis of the proposed optimized approach based on error correction metric it is inferred that it improves the accuracy against existing algorithms in terms of variable anchor ratio, node number and the range towards the localization error.

ACS Style

Deepak Prashar; Dilip Kumar. Performance Evaluation of the Optimized Error Correction Based Hop Localization Approach in a Wireless Sensor Network. Wireless Personal Communications 2019, 111, 2517 -2543.

AMA Style

Deepak Prashar, Dilip Kumar. Performance Evaluation of the Optimized Error Correction Based Hop Localization Approach in a Wireless Sensor Network. Wireless Personal Communications. 2019; 111 (4):2517-2543.

Chicago/Turabian Style

Deepak Prashar; Dilip Kumar. 2019. "Performance Evaluation of the Optimized Error Correction Based Hop Localization Approach in a Wireless Sensor Network." Wireless Personal Communications 111, no. 4: 2517-2543.

Conference paper
Published: 17 November 2019 in Advances in Intelligent Systems and Computing
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Internet of Things (IoT) always has various issues because of its heterogeneous nature and thus is not very effective while accommodating the authentication mechanisms. To resolve this issue of authentication of the nodes involved in a particular application, a middleware has been proposed in this paper. This proposed middleware acts as a gateway between IoT devices and provides the user the ability of node authentication in wireless sensor network (WSN). When a node or a user accesses the network at any time, it is verified by the middleware. It is also capable to handle the heterogeneous messages which are the main challenge in IoT. By executing proposed framework, interoperability issue between IoT networks can be resolved.

ACS Style

Deepak Prashar; Ranbir Singh Batth; Atul Malhotra; Kavita; Varam Sudhakar; Bhupinder Kaur. Node Authentication in IoT-Enabled Sensor Network Using Middleware. Advances in Intelligent Systems and Computing 2019, 125 -135.

AMA Style

Deepak Prashar, Ranbir Singh Batth, Atul Malhotra, Kavita, Varam Sudhakar, Bhupinder Kaur. Node Authentication in IoT-Enabled Sensor Network Using Middleware. Advances in Intelligent Systems and Computing. 2019; ():125-135.

Chicago/Turabian Style

Deepak Prashar; Ranbir Singh Batth; Atul Malhotra; Kavita; Varam Sudhakar; Bhupinder Kaur. 2019. "Node Authentication in IoT-Enabled Sensor Network Using Middleware." Advances in Intelligent Systems and Computing , no. : 125-135.

Conference paper
Published: 01 July 2019 in 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT)
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Wireless Sensor Network (WSN) contains the many sensing nodes that work together in the network to achieve a common goal. Localization means to know the position of the sensor node in the WSN. Various schemes are available designed by different authors for the localization of the sensor node categorized in to range based and range free schemes. All of the schemes available for the localization have some benefits and pitfalls. So we have proposed a new approach in this paper that is both range free and distributed. In this we are using the Basic Dv-Hop algorithm for the node localization with some changes. After implementing the algorithm, we analyzed the new algorithm that was proposed to produce the best results as collate to basic DV-Hop and improved DV-Hop. We collated our algorithm with localization error corresponding to three parameters such as: anchor nodes, number of nodes and range of the node.

ACS Style

Bhupinder Kaur; Deepak Prashar. Analysis of Improved DV-Hop Algorithm with Distance Error. 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT) 2019, 1, 1242 -1246.

AMA Style

Bhupinder Kaur, Deepak Prashar. Analysis of Improved DV-Hop Algorithm with Distance Error. 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT). 2019; 1 ():1242-1246.

Chicago/Turabian Style

Bhupinder Kaur; Deepak Prashar. 2019. "Analysis of Improved DV-Hop Algorithm with Distance Error." 2019 2nd International Conference on Intelligent Computing, Instrumentation and Control Technologies (ICICICT) 1, no. : 1242-1246.

Article
Published: 12 March 2019 in Wireless Personal Communications
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In the various applications where the wireless sensor network (WSN) is deployed all the sensor nodes work collectively for a particular task. It is useful in various applications as in the military, medical, home related to monitoring human body activities also. As in WSN, sensors sense the environment and this sensing is not useful until the exact location of the sensor is not known. So in WSN, localization is an important task. Mainly, there are two types of algorithms that are available for localization, range based and free range. All of these algorithms are differentiated on the basis of one common factor that is the localization error. Under the range free localization approach most explored algorithm is a distance vector (DV) Hop. In this paper, a new distance error correction metric based algorithm is proposed to minimize the error that exists in the basic hop based algorithms. It has been implemented in MATLAB for the results verification and comparison. Moreover, the performance of the proposed algorithm is analyzed for various factors like the average localization error, error variance and accuracy in accordance to the parameters like the total node amount, the anchor node amount and range. Simulation results conclude that the proposed error correction based approach presented in this paper performed exceptionally well against the basic DV Hop, improved DV(IDV) Hop and particle swarm optimization based DV Hop and thus improves the overall localization process of the whole network.

ACS Style

Deepak Prashar; Kiran Jyoti. Distance Error Correction Based Hop Localization Algorithm for Wireless Sensor Network. Wireless Personal Communications 2019, 106, 1465 -1488.

AMA Style

Deepak Prashar, Kiran Jyoti. Distance Error Correction Based Hop Localization Algorithm for Wireless Sensor Network. Wireless Personal Communications. 2019; 106 (3):1465-1488.

Chicago/Turabian Style

Deepak Prashar; Kiran Jyoti. 2019. "Distance Error Correction Based Hop Localization Algorithm for Wireless Sensor Network." Wireless Personal Communications 106, no. 3: 1465-1488.

Review
Published: 28 November 2018 in Communications in Computer and Information Science
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Wireless Sensor Network (WSN) is made up of huge no. of sensing nodes those are known as sensor nodes. In WSN Localization for the unknown nodes, is significant task. Various techniques are available to solve this problem. Two main categories are rough and excellent. Rough categories require less detail to determine the position of unknown node, easy to implement and less complex and the excellent technique require more detail to determine the position and provide the accuracy about position of the node. In this review paper we are presenting the analysis of various localization algorithms and providing the comparison of performances and approaches.

ACS Style

Bhupinder Kaur; Deepak Prashar. Analysis and Comparison of Localization Approaches in WSN: A Review. Communications in Computer and Information Science 2018, 294 -309.

AMA Style

Bhupinder Kaur, Deepak Prashar. Analysis and Comparison of Localization Approaches in WSN: A Review. Communications in Computer and Information Science. 2018; ():294-309.

Chicago/Turabian Style

Bhupinder Kaur; Deepak Prashar. 2018. "Analysis and Comparison of Localization Approaches in WSN: A Review." Communications in Computer and Information Science , no. : 294-309.

Research article
Published: 22 October 2018 in Transactions on Emerging Telecommunications Technologies
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Localization error is the main criteria to decide the efficiency on any localization approach. In case of range‐free hop‐based localization approaches, position coordinates estimation is done through the common steps like the calculation of the minimum hop count, hop size, and then later on applying the multilateration or least square approach. There are many improvements that have been made in the form of various algorithms through some changes in the common steps for the reduction of localization error. It has been observed that the existing algorithms are still having the highest value of localization error. To overcome the deficiencies in the existing algorithms, a novel distance error correction metric–based approach has been introduced. This paper presents a distance error correction–based algorithm (DEC‐hop) for the hop‐based localization approach for a wireless sensor network. Distance‐based error correction factor that is introduced in this paper further reduces the localization error value to some extent. For measuring the effectiveness and the preciseness of the given approach, it is inspected with other improved algorithms based on DV‐hop. Simulation results have confirmed that the proposed error correction–based algorithm outperforms the other variety of improved hop‐based algorithms. Results are analyzed in terms of various factors like the localization error, accuracy, and error variance against the parameters of interest taken as node amount, anchor ratio, and communication range of the node.

ACS Style

Deepak Prashar; Kiran Jyoti; Dilip Kumar. Design and analysis of distance error correction–based localization algorithm for wireless sensor networks. Transactions on Emerging Telecommunications Technologies 2018, 29, e3547 .

AMA Style

Deepak Prashar, Kiran Jyoti, Dilip Kumar. Design and analysis of distance error correction–based localization algorithm for wireless sensor networks. Transactions on Emerging Telecommunications Technologies. 2018; 29 (12):e3547.

Chicago/Turabian Style

Deepak Prashar; Kiran Jyoti; Dilip Kumar. 2018. "Design and analysis of distance error correction–based localization algorithm for wireless sensor networks." Transactions on Emerging Telecommunications Technologies 29, no. 12: e3547.

Journal article
Published: 01 August 2018 in International Journal of Advances in Applied Sciences
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Advancements in wireless communication technology have empowered the researchers to develop large scale wireless networks with huge number of sensor nodes. In these networks localization is very active field of research. Localization is a way to determine the physical position of sensor nodes which is useful in many aspects such as to find the origin of events, routing and network coverage. Locating nodes with GPS systems is expensive, power consuming and not applicable to indoor environments. Localization in three dimensional space and accuracy of the estimated location are two factors of major concern. In this paper, a new three dimensional Distributed range-free algorithm which is known as CP-NR is proposed. This algorithm has high localization accuracy and resolved the problem of existing NR algorithm. CP-NR (Coplanar and Projected Node Reproduction) algorithm makes use of co-planarity and projection of point on plane concepts to reduce the localization error. Results have shown that CP-NR algorithm is superior to NR algorithm and comparison is done for the localization accuracy with respect to variations in range, anchor density and node density.

ACS Style

Deepak Prashar; Kiran Jyoti; Dilip Kumar. CP-NR Distributed Range Free Localization Algorithm in WSN. International Journal of Advances in Applied Sciences 2018, 7, 212 -219.

AMA Style

Deepak Prashar, Kiran Jyoti, Dilip Kumar. CP-NR Distributed Range Free Localization Algorithm in WSN. International Journal of Advances in Applied Sciences. 2018; 7 (3):212-219.

Chicago/Turabian Style

Deepak Prashar; Kiran Jyoti; Dilip Kumar. 2018. "CP-NR Distributed Range Free Localization Algorithm in WSN." International Journal of Advances in Applied Sciences 7, no. 3: 212-219.

Conference paper
Published: 11 April 2018 in Advances in Intelligent Systems and Computing
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Numerous applications such as Internet of Things and robotics using sensors and wireless sensor networks (WSN) require localization and target tracking for their efficient implementation and functioning. Localization means determining the precise position of nodes within the network. Localization sometimes is also a precondition to other functionalities such as routing, self-organization capability. Various approaches and algorithms have been proposed to solve the localization problem. Most of these techniques involve use of some deployed nodes whose position coordinates are already known to us (using GPS or some other method) called landmarks or anchors. This paper presents a novel connectivity-based mobile localization approach for sensor networks and list of parameters on which a comparative study can be done.

ACS Style

Abhishek Kumar; Deepak Prashar. A Novel Approach for Node Localization in Wireless Sensor Networks. Advances in Intelligent Systems and Computing 2018, 419 -428.

AMA Style

Abhishek Kumar, Deepak Prashar. A Novel Approach for Node Localization in Wireless Sensor Networks. Advances in Intelligent Systems and Computing. 2018; ():419-428.

Chicago/Turabian Style

Abhishek Kumar; Deepak Prashar. 2018. "A Novel Approach for Node Localization in Wireless Sensor Networks." Advances in Intelligent Systems and Computing , no. : 419-428.

Conference paper
Published: 11 April 2018 in Advances in Intelligent Systems and Computing
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The wireless body area network is part of wireless sensor network in which both indoor and outdoor patients are monitored using sensors and wireless technology. The critical phase of monitoring is transmission of real time data from remote location to hospital community cloud, when patients outside the hospital at some remote location and is connected hospital cloud using Internet connection. So there is need to encrypt the data collected by sensor from patient before transmission. The paper is presenting the new concept, hybrid encryption algorithm (HEA) that is suitable for ad hoc as well as for wired networks also. The algorithm not only considers security of data but also the various constraints of sensor networks like battery power, bandwidth, limited processing capability, dynamic topology.

ACS Style

Sameer Farooq; Deepak Prashar; Kiran Jyoti. Hybrid Encryption Algorithm in Wireless Body Area Networks (WBAN). Advances in Intelligent Systems and Computing 2018, 401 -410.

AMA Style

Sameer Farooq, Deepak Prashar, Kiran Jyoti. Hybrid Encryption Algorithm in Wireless Body Area Networks (WBAN). Advances in Intelligent Systems and Computing. 2018; ():401-410.

Chicago/Turabian Style

Sameer Farooq; Deepak Prashar; Kiran Jyoti. 2018. "Hybrid Encryption Algorithm in Wireless Body Area Networks (WBAN)." Advances in Intelligent Systems and Computing , no. : 401-410.