IoT is a revolutionary technology that represents the future of computing and communications. Most of the people over all worlds depend on agriculture. Because of this reason smart IT technologies are needed to migrate with traditional agriculture methods. Using modern technologies can control the cost, maintenance and monitoring performance. Satellite and aerial imagery play a vital role in modern agriculture. Precision agriculture sensor monitoring network is used greatly to measure agri-related information like temperature, humidity, soil PH, soil nutrition levels, water level etc. so, with IoT farmers can remotely monitor their crop and equipment by phones and computers. In this paper, we surveyed some typical applications of Agriculture IoT Sensor Monitoring Network technologies using Cloud computing as the backbone. This survey is used to understand the different technologies and to build sustainable smart agriculture. Simple IoT agriculture model is addressed with a wireless network. © 2017 IEEE.

Viswanathan P

School of Computer Science and Engineering

Chennai Campus

Mahammad Shareef Mekala

Vellore Institute of Technology (VIT) is a private university located in&nbsp;Tamil Nadu, India. Founded in 1984, as Vellore Engineering College, the institution offers 20 undergraduate, 34 postgraduate, four integrated and four research programs. It has campuses in Vellore, Amravati, Bhopal and Chennai.

VIT is one of the top ranked private universities in India according to NIRF, THE and QS Rankings.&nbsp;Govt. of India has recognized&nbsp;VIT, Vellore as an&nbsp;Institution of Eminence. This has allowed VIT to take independent quality initiatives and move up in world ranking.

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VIT University

2017 International conference on Microelectronic Devices, Circuits and Systems (ICMDCS)

Cloud computing (CC) enables enumerable services to manipulate sensor data generated from X-internet of things (IoT) applications. It is accomplished by selecting an accurate decision-making system, sensors, and VMs. This paper reviews energy-efficient sensor, resource-based VM selection approaches for X-IoT applications. It is prompted to distinguish measurement functions, architectures, VM scheduling mechanism challenges. The first field was surveyed to identify the technical measurement variables of agriculture and the second field to distinguish the difficulties of sensor selection, communication impact on the rate of sensor data generation. The last field represents VM consolidation approaches based on a type of task, resource, and energy utilization rate impact on balancing the resources of VMs during sudden changes in the network field. The precise implementation details of selected articles are bounded with sensor energy consumption, edge computing modules, and communication strategies. The outcomes of investigation consolidate a sensor-cloud framework that implies prevailing solution to CC for X-IoT. © 2018, © 2018 Informa UK Limited, trading as Taylor & Francis Group.

International Journal of Computers and Applications

A survey: energy-efficient sensor and VM selection approaches in green computing for X-IoT applications

IoT leads to abrupt variations producing an immense number of data streams for storage, which is a considerable task in the heterogeneous cloud computing environment. Extant techniques consider task deadlines for virtual machine (VM) allocation and migration. This creates a resource famine leading to haphazard and numerous VM migrations, high energy consumption and unbalanced resource utilization. To solve this issue, an energy-efficient resource ranking and utilization factor-based virtual machine selection (ERVS) approach is proposed. ERVS encompasses the resource requirement rate for task classification, comprehensive resource balance ranking, processing element cost and the resource utilization square model for migration. It evaluates overloaded and underloaded hosts and types of VM by predicting CPU utilization rate and energy consumption. Based on this, tasks are sorted and VMs are optimally assigned, which enhances the resource utilization rate, reducing the number of live VM migrations. The experiments evaluate the ability of the proposed approach to diminish energy consumption without violation of service level agreements. © 2018 Elsevier Ltd

Computers & Electrical Engineering

Energy-efficient virtual machine selection based on resource ranking and utilization factor approach in cloud computing for IoT

The Internet of things concept is based on data from sensor devices. The conservation of sensor data in the cloud has become a well-known challenge with respect to the sensor-cloud network. There is an enormous quantity of sensed data, including missed and unimportant data due to unavailability of the node, low link quality, node deficiency or latency in path communication. In order to address this issue, it is necessary to develop an accurate sensor selection approach, precisely for the purpose of reducing the quantity of unimportant data (missed and noisy data). In this paper, we formulate an innovative and efficient bi-level node energy assessment algorithm, named BNSA, which uses a belief propagation protocol for optimal energy-efficient sensor selection. On the first level, the equilibrium transmission energy function is applied to all nodes to evaluate the transmission rate and link quality, together with the residual energy of the node, to predict the energy consumption, providing an accurate prediction of the energy level of the nodes. On the second level, optimal nodes are selected based on the prediction of the energy level. Belief propagation draws inferences for revealing missed sensor data. This approach improves the lifespan of the network and reduces the energy utilization rate by more than 32.3% with a delay rate of 77%. This is reflected in an enhancement of the quality of service with 85% of the energy consumption over the network, compared with existing models. © 2019, Springer Science+Business Media, LLC, part of Springer Nature.

Wireless Personal Communications

Equilibrium Transmission Bi-level Energy Efficient Node Selection Approach for Internet of Things

2019 International Conference on contemporary Computing and Informatics (IC3I)

Accurate Decision-making System for Mining Environment using Li-Fi 5G Technology over IoT Framework

International Journal of Engineering and Advanced Technology Regular Issue

Optimal Sensor Deployment in Internet of Things based Wireless Sensor Network for Irrigation Management System

Smart Diagnosis of Orthopaedic Disorders using Internet of Things (IoT)

2016 Electrical Engineering Conference (EECon)

Smart irrigation controlling system for green roofs based on predicted evapotranspiration

2016 International Conference on Computation System and Information Technology for Sustainable Solutions (CSITSS)

Implementation of IoT (Internet of Things) and Image processing in smart agriculture

2016 International Conference on Information Technology Systems and Innovation (ICITSI)

Sensor networks data acquisition and task management for decision support of smart farming

A Survey: Smart agriculture IoT with cloud computing

Journal	Data powered by Typeset2017 International conference on Microelectronic Devices, Circuits and Systems (ICMDCS)
Publisher	Data powered by TypesetIEEE
Open Access	No