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Big and Meta Data Management for U-Agriculture Mobile Services
Chandra Sukanya Nandyala,Haeng-Kon Kim 보안공학연구지원센터(IJSEIA) 2016 International Journal of Software Engineering and Vol.10 No.2
Big Data is a huge amount of data generated continuously and it extracts the meaning, structure, and relationships in enormously large data sets. Metadata is defined as data about data, where is comes from, and when it was taken etc. Metadata is a supplementary data and is generally related with a certain piece of data (big data) that is more important. Metadata helps in making value added decisions and information about own data travelling for big data. This paper communicates about big data, metadata and their management associated to u-agriculture mobile services and lime lights more on sensors that are integrated and built-in. B&M (Big and Meta) data management is very challenging and is strong topic for research currently. Firstly, this paper reviews B&M data and their management. Also presents relationship between big data and Metadata and challenges. And also types of sensors, techniques, technologies, applications, and advantages of various types of sensors for u-agriculture mobile services in their decision making. Finally presents architecture for U-Agriculture Mobile Services based on Sensor-Cloud Infrastructure which helps not only farms and also applications, services provides and organisations in management of B&M data.
From Cloud to Fog and IoT-Based Real-Time U-Healthcare Monitoring for Smart Homes and Hospitals
Chandra Sukanya Nandyala,Haeng-Kon Kim 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.2
Healthcare in the past, decision making was merely based on doctor’s personal experience, domain knowledge, patient's physical signs and symptoms and diagnostic laboratory reports. In contrast, devices or things and technologies came into existence playing significant role and helps doctors or physicians to add wisdom to their decision in healthcare monitoring. Cloud paradigm stands as the backbone for on-demand network use of a shared pool of configurable computing resources (e.g., networks, servers, storage, applications, and services) in U-healthcare monitoring system architectures but attached limitations which are solved by Fog(significant extension of cloud). This paper proposed architecture for IoT based u-healthcare monitoring with the motivation and advantages of Cloud to Fog(C2F) computing which interacts more by serving closer to the edge (end points) at smart Homes and Hospitals.
Green IoT Agriculture and HealthcareApplication (GAHA)
Chandra Sukanya Nandyala,Haeng-Kon Kim 보안공학연구지원센터 2016 International Journal of Smart Home Vol.10 No.4
The application of the two trending and popular technologies, Cloud Computing (CC) and the Internet of Things (IoT) are current hot discussions in the field of agriculture and healthcare applications. Motivated by achieving a sustainable world, this paper discusses various technologies and issues regarding green cloud computing and green Internet of Things, further improves the discussion with the reduction in energy consumption of the two techniques (CC and IoT) combination in agriculture and healthcare systems. The history and concept of the hot green information and communications technologies (ICT’s) which are enabling green IoT will be discussed. Green computing introduction first and later focuses on the recent works done regarding the two emerging technologies in both agriculture and healthcare cases. Furthermore, this paper contributes by presenting Green IoT Agriculture and Healthcare Application (GAHA) using sensor-cloud integration model. Finally, lists out the advantages, challenges, and future research directions related to green application design. Our research aims to make green area broad and contribution to sustainable application world.
A Q-learning-based Opportunistic Routing Protocol for Internet of Underwater Things
Chandra Sukanya Nandyala,Ho-Shin Cho 한국통신학회 2021 한국통신학회 학술대회논문집 Vol.2021 No.11
This short paper proposes a Q-learning-based opportunistic routing protocol to prolong the network lifetime of the Internet of Underwater Things (IoUT). The proposed protocol exploits the broadcasting feature of opportunistic routing to obtain real-time updates of changes in the topology and to determine the list of the potential next-forwarders (PNFs). Using Q-learning, a PNF can learn if it should become the next-forwarder. Further discussions on the unaddressed issues, such as, network partitioning and hidden node, are provided.
Rice, Kevin M.,Nalabotu, Siva K.,Manne, Nandini D.P.K.,Kolli, Madhukar B.,Nandyala, Geeta,Arvapalli, Ravikumar,Ma, Jane Y.,Blough, Eric R. The Korean Society for Preventive Medicine 2015 예방의학회지 Vol.48 No.3
Objectives: With recent advances in nanoparticle manufacturing and applications, potential exposure to nanoparticles in various settings is becoming increasing likely. No investigation has yet been performed to assess whether respiratory tract exposure to cerium oxide ($CeO_2$) nanoparticles is associated with alterations in protein signaling, inflammation, and apoptosis in rat lungs. Methods: Specific-pathogen-free male Sprague-Dawley rats were instilled with either vehicle (saline) or $CeO_2$ nanoparticles at a dosage of 7.0 mg/kg and euthanized 1, 3, 14, 28, 56, or 90 days after exposure. Lung tissues were collected and evaluated for the expression of proteins associated with inflammation and cellular apoptosis. Results: No change in lung weight was detected over the course of the study; however, cerium accumulation in the lungs, gross histological changes, an increased Bax to Bcl-2 ratio, elevated cleaved caspase-3 protein levels, increased phosphorylation of p38 MAPK, and diminished phosphorylation of ERK-1/2-MAPK were detected after $CeO_2$ instillation (p<0.05). Conclusions: Taken together, these data suggest that high-dose respiratory exposure to $CeO_2$ nanoparticles is associated with lung inflammation, the activation of signaling protein kinases, and cellular apoptosis, which may be indicative of a long-term localized inflammatory response.