scholarly journals An In-Networking Double-Layered Data Reduction for Internet of Things (IoT)

Sensors ◽  
2019 ◽  
Vol 19 (4) ◽  
pp. 795 ◽  
Author(s):  
Waleed Ismael ◽  
Mingsheng Gao ◽  
Asma Al-Shargabi ◽  
Ammar Zahary
Keyword(s):  
Internet Of Things ◽  
Data Reduction ◽  
Specific Area ◽  
Base Station ◽  
Sensor Nodes ◽  
Data Filtering ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Network Bandwidth ◽  
The Internet Of Things

Due to the ever-increasing number and diversity of data sources, and the continuous flow of data that are inevitably redundant and unused to the cloud, the Internet of Things (IoT) brings several problems including network bandwidth, the consumption of network energy, cloud storage, especially for paid volume, and I/O throughput as well as handling huge amount of stored data in the cloud. These call for data pre-processing at the network edge before data transmission over the network takes place. Data reduction is a method for mitigating such problems. Most state-of-the-art data reduction approaches employ a single tier, such as gateways, or two tiers, such gateways and the cloud data center or sensor nodes and base station. In this paper, an approach for IoT data reduction is proposed using in-networking data filtering and fusion. The proposed approach consists of two layers that can be adapted at either a single tier or two tiers. The first layer of the proposed approach is the data filtering layer that is based on two techniques, namely data change detection and the deviation of real observations from their estimated values. The second layer is the data fusion layer. It is based on a minimum square error criterion and fuses the data of the same time domain for specific sensors deployed in a specific area. The proposed approach was implemented using Python and the evaluation of the approach was conducted based on a real-world dataset. The obtained results demonstrate that the proposed approach is efficient in terms of data reduction in comparison with Least Mean Squares filter and Papageorgiou’s (CLONE) method.

scholarly journals Towards a Low-Cost Precision Viticulture System Using Internet of Things Devices

IoT ◽  
2020 ◽  
Vol 1 (1) ◽  
pp. 5-20 ◽  
Author(s):  
Petros Spachos
Keyword(s):  
Internet Of Things ◽  
Precision Agriculture ◽  
Low Cost ◽  
Base Station ◽  
Sensor Nodes ◽  
Wireless Sensor Nodes ◽  
Precision Viticulture ◽  
Iot Devices ◽  
Agricultural Areas ◽  
The Internet Of Things

Precision Agriculture (PA) is an ever-expanding field that takes modern technological advancements and applies it to farming practices to reduce waste and increase output. One advancement that can play a significant role in achieving precision agriculture is wireless technology, and specifically the Internet of Things (IoT) devices. Small, inch scale and low-cost devices can be used to monitor great agricultural areas. In this paper, a system for precision viticulture which uses IoT devices for real-time monitoring is proposed. The different components of the system are programmed properly and the interconnection between them is designed to minimize energy consumption. Wireless sensor nodes measure soil moisture and soil temperature in the field and transmit the information to a base station. If the conditions are optimal for a disease or pest to occur, a drone flies towards the area. When the drone is over the node, pictures are captured and then it returns to the base station for further processing. The feasibility of the system is examined through experimentation in a realistic scenario.

scholarly journals A Framework for Agricultural Pest and Disease Monitoring Based on Internet-of-Things and Unmanned Aerial Vehicles

Sensors ◽  
2020 ◽  
Vol 20 (5) ◽  
pp. 1487 ◽  
Author(s):  
Demin Gao ◽  
Quan Sun ◽  
Bin Hu ◽  
Shuo Zhang
Keyword(s):  
Internet Of Things ◽  
Unmanned Aerial Vehicles ◽  
Sensor Nodes ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Pests And Diseases ◽  
Aerial Vehicles ◽  
Sensing Technology ◽  
Weather Parameters ◽  
Iot Devices

With the development of information technology, Internet-of-Things (IoT) and low-altitude remote-sensing technology represented by Unmanned Aerial Vehicles (UAVs) are widely used in environmental monitoring fields. In agricultural modernization, IoT and UAV can monitor the incidence of crop diseases and pests from the ground micro and air macro perspectives, respectively. IoT technology can collect real-time weather parameters of the crop growth by means of numerous inexpensive sensor nodes. While depending on spectral camera technology, UAVs can capture the images of farmland, and these images can be utilize for analyzing the occurrence of pests and diseases of crops. In this work, we attempt to design an agriculture framework for providing profound insights into the specific relationship between the occurrence of pests/diseases and weather parameters. Firstly, considering that most farms are usually located in remote areas and far away from infrastructure, making it hard to deploy agricultural IoT devices due to limited energy supplement, a sun tracker device is designed to adjust the angle automatically between the solar panel and the sunlight for improving the energy-harvesting rate. Secondly, for resolving the problem of short flight time of UAV, a flight mode is introduced to ensure the maximum utilization of wind force and prolong the fight time. Thirdly, the images captured by UAV are transmitted to the cloud data center for analyzing the degree of damage of pests and diseases based on spectrum analysis technology. Finally, the agriculture framework is deployed in the Yangtze River Zone of China and the results demonstrate that wheat is susceptible to disease when the temperature is between 14 °C and 16 °C, and high rainfall decreases the spread of wheat powdery mildew.

scholarly journals Review of Energy Efficient Techniques of IoT

2019 ◽  
Vol 7 (5) ◽  
pp. 17-21 ◽  
Author(s):  
Ritesh Awasthi ◽  
Navneet Kaur
Keyword(s):  
Energy Consumption ◽  
Internet Of Things ◽  
Energy Efficient ◽  
Research Work ◽  
Base Station ◽  
Sensor Nodes ◽  
Dynamic Nature ◽  
Work Related ◽  
Reduce Energy Consumption ◽  
The Internet Of Things

The network across which the information is sensed by the sensor devices and then forwarded to the sink is known as Internet of Things (IoT). Even though this system is deployed in several applications, there are certain issues faced in it due to its dynamic nature. The internet of things is derived from the wireless sensor networks. The sensor nodes which are deployed to sense environmental conditions are very small in size and also deployed on the far places due to which energy consumption is the major issue of internet of things. This research work related to reduce energy consumption of the network so that lifetime can be improved. In the existing system the approach of multilevel clustering is used for the data aggregation to base station. In the approach of multilevel clustering, the whole network is divided into clusters and cluster heads are selected in each cluster. The energy efficient techniques of internet of things are reviewed and analyzed in terms of certain parameters.

scholarly journals Exploiting cooperative sensing for accurate target tracking in industrial Internet of things

2019 ◽  
Vol 15 (12) ◽  
pp. 155014771989220 ◽  
Author(s):  
Muneeb A Khan ◽  
Muazzam A Khan ◽  
Anis U Rahman ◽  
Asad Waqar Malik ◽  
Safdar A Khan
Keyword(s):  
Internet Of Things ◽  
Target Tracking ◽  
Base Station ◽  
Sensor Nodes ◽  
Tracking Accuracy ◽  
Industrial Internet ◽  
Target Path ◽  
The Internet Of Things ◽  
Localization And Tracking ◽  
Complete Path

Wireless sensor networks are a cornerstone of the Internet of things with many applications. An important aspect of such applications is target tracking using self-positioned known sensor nodes. Over the years, many schemes have been proposed to locate and track the target path. However, accuracy and reliable tracking remain an open area of research. In this article, we propose a dynamic cooperative multilateral sensing scheme for indoor industrial environments to improve target localization and tracking accuracy. The scheme is designed to select reliable nodes based on the distance between nodes within-cluster and to the target for reduced positioning error. Furthermore, a cluster node is dynamically selected based on distance from the base station. We simulate the proposed technique in scenarios with tracking at regular intervals and with the complete path. Furthermore, the performance of the scheme is also tested under different sensor coverage areas. The results show that the proposed scheme provides better target tracking with up to 19% higher accuracy in comparison to the traditional trilateration scheme.

scholarly journals Client Aware Scalable Cloudlet to Augment Edge Computing with Mobile Cloud Migration Service

2020 ◽  
Vol 14 (12) ◽  
pp. 165
Author(s):  
Uma Nandhini D ◽  
Udhayakumar S ◽  
Latha Tamilselvan ◽  
Silviya Nancy J
Keyword(s):  
Wireless Lan ◽  
High Speed ◽  
Virtual Machines ◽  
Linear Regression Analysis ◽  
Mobile Cloud ◽  
Cloud Data Center ◽  
Cloud Data ◽  
Battery Lifetime ◽  
Network Bandwidth ◽  
Load Conditions

<p class="0abstract">Computing with mobile is still in its infancy due to its limitations of computational power, battery lifetime and storage capacity. These limitations hinder the growth of mobile computing, which in-turn affects the growth of computationally intensive applications developed for the mobile devices. So in-order to help execute complex applications within the mobile device, mobile cloud computing (MCC) emerged as a feasible solution. The job of offloading the task to the cloud data center for storage and execution from the mobile seems to gain popularity, however, issues related to network bandwidth, loss of mobile data connectivity, and connection setup does not augment well to extend the benefits offered by MCC. Cloudlet servers filled this gab by assisting the mobile cloud environment as an edge device, offering compute power to the connected devices with high speed wireless LAN connectivity. Implementation constraints of cloudlet faces severe challenges in-terms of its storage, network sharing, and VM provisioning. Moreover, the number of connected devices of the cloudlet and its load conditions vary drastically leading to unexpected bottleneck, in which case the availability to server becomes an issue. Therefore, a scalable cloudlet, Client Aware Scalable Cloudlet (CASC) is proposed with linear regression analysis, predicting the knowledge of expected load conditions for provisioning new virtual machines and to perform resource migration.</p>

scholarly journals Forest Fire Prevention Using WSN Assisted IOT

2018 ◽  
Vol 7 (3.12) ◽  
pp. 1317 ◽  
Author(s):  
Vrince Vimal ◽  
Madhav Ji Nigam
Keyword(s):  
Internet Of Things ◽  
Sensor Network ◽  
Forest Fire ◽  
Clustering Algorithm ◽  
Base Station ◽  
Sensor Nodes ◽  
Fire Prevention ◽  
New Era ◽  
Data Flows ◽  
Forest Fire Prevention

Internet of Things is the mainstay of the new era since its application becomes the future of day-to-day life. This work targets the IoT network assisted by WSN to prevent forest fire. We propose two-layer architecture of sensor network assisted by IoT enabled UAVs. The data flows in the proposed architecture in bottom-up fashion i.e., data is sensed by the nodes, which are deployed in the forest area (and sense temperature continuously). This data is transmitted to upper layer consisting of UAVs, which take appropriate action (to sprinkle water to bring temperature down to prevent fire). All the UAVs are interconnected to each other as well as to base station. The sensor nodes are clustered using two-step clustering algorithm, which takes care of the isolated nodes. The scheme has been equated to another WSN assisted IoT clustering technique. The proposed scheme outperforms the existing in terms of congestion at the UAV stations, number of alive nodes and remaining energy of the network.  

scholarly journals Beamforming Optimization in Internet of Things Applications Using Robust Swarm Algorithm in Conjunction with Connectable and Collaborative Sensors

Sensors ◽  
2020 ◽  
Vol 20 (7) ◽  
pp. 2048 ◽  
Author(s):  
Mohammed Zaki Hasan ◽  
Hussain Al-Rizzo
Keyword(s):  
Internet Of Things ◽  
Antenna Arrays ◽  
Smart Grids ◽  
Network Connectivity ◽  
Base Station ◽  
Node Selection ◽  
Swarm Optimization ◽  
Selection Scheme ◽  
Multihop Relaying ◽  
The Internet Of Things

The integration of the Internet of Things (IoT) with Wireless Sensor Networks (WSNs) typically involves multihop relaying combined with sophisticated signal processing to serve as an information provider for several applications such as smart grids, industrial, and search-and-rescue operations. These applications entail deploying many sensors in environments that are often random which motivated the study of beamforming using random geometric topologies. This paper introduces a new algorithm for the synthesis of several geometries of Collaborative Beamforming (CB) of virtual sensor antenna arrays with maximum mainlobe and minimum sidelobe levels (SLL) as well as null control using Canonical Swarm Optimization (CPSO) algorithm. The optimal beampattern is achieved by optimizing the current excitation weights for uniform and non-uniform interelement spacings based on the network connectivity of the virtual antenna arrays using a node selection scheme. As compared to conventional beamforming, convex optimization, Genetic Algorithm (GA), and Particle Swarm Optimization (PSO), the proposed CPSO achieves significant reduction in SLL, control of nulls, and increased gain in mainlobe directed towards the desired base station when the node selection technique is implemented with CB.

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