EQL: Event Query Language for the Sharing of Internet-of-Things Infrastructure and Collaborative Applications Development

2017 ◽  
pp. 73-78 ◽  
Author(s):  
Kutalmış Akpınar ◽  
Kien A. Hua
Keyword(s):  
Internet Of Things ◽  
Query Language ◽  
Collaborative Applications

scholarly journals Data Query Mechanism Based on Hash Computing Power of Blockchain in Internet of Things

Sensors ◽  
2019 ◽  
Vol 20 (1) ◽  
pp. 207 ◽  
Author(s):  
Yongjun Ren ◽  
Fujian Zhu ◽  
Pradip Kumar Sharma ◽  
Tian Wang ◽  
Jin Wang ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Smart Grids ◽  
Query Language ◽  
Bloom Filter ◽  
Reading Performance ◽  
Computational Power ◽  
Computing Power ◽  
Data Query ◽  
Internet Of Things Environment ◽  
The Internet Of Things

In the IoT (Internet of Things) environment, smart homes, smart grids, and telematics constantly generate data with complex attributes. These data have low heterogeneity and poor interoperability, which brings difficulties to data management and value mining. The promising combination of blockchain and the Internet of things as BCoT (blockchain of things) can solve these problems. This paper introduces an innovative method DCOMB (dual combination Bloom filter) to firstly convert the computational power of bitcoin mining into the computational power of query. Furthermore, this article uses the DCOMB method to build blockchain-based IoT data query model. DCOMB can implement queries only through mining hash calculation. This model combines the data stream of the IoT with the timestamp of the blockchain, improving the interoperability of data and the versatility of the IoT database system. The experiment results show that the random reading performance of DCOMB query is higher than that of COMB (combination Bloom filter), and the error rate of DCOMB is lower. Meanwhile, both DCOMB and COMB query performance are better than MySQL (My Structured Query Language).

Detection and Regulation of Soil Moisture and Nutrients Using Cloud Computing and Internet of Things in Agriculture

2019 ◽  
Vol 16 (8) ◽  
pp. 3183-3186
Author(s):  
A. Aiswarya ◽  
Reshmi Anantapalli ◽  
Ria Singh ◽  
S. Nandhini
Keyword(s):  
Cloud Computing ◽  
Soil Moisture ◽  
Internet Of Things ◽  
Electrochemical Sensors ◽  
Query Language ◽  
Liquid Crystal Display ◽  
Supply System ◽  
Soil Monitoring ◽  
Irrigation Systems ◽  
Major Drawback

Deficiency in fresh water resources globally has been a serious problem in the last decade. For overcoming this major drawback in the irrigation systems, smart soil monitoring system is implemented. The paper focuses on detection of moisture and nutrient levels present within the soil using moisture sensors and electrochemical sensors. These sensors are connected to Arduino board which controls the automatic water supply system which operates automatically based on the signal received from the Arduino board. Data received from Arduino board is displayed on a Liquid Crystal Display screen. The data collected will be stored in a cloud via an Internet of Things gateway. The system will also suggest the kinds of crops, from the list of crops stored in an Structured Query Language database, that will be best suitable for that soil based on the levels of soil moisture and nutrients detected.

Incorporating Spatial Queries into Semantic Sensor Streams on the Internet of Things

2017 ◽  
Vol 28 (4) ◽  
pp. 24-39 ◽  
Author(s):  
Sungkwang Eom ◽  
Kyong-Ho Lee
Keyword(s):  
Internet Of Things ◽  
Query Language ◽  
Vital Role ◽  
The Internet ◽  
Observation Data ◽  
Temporal Properties ◽  
Efficient Management ◽  
Tremendous Amount ◽  
Spatiotemporal Queries ◽  
The Internet Of Things

In the Internet of Things (IoT) environment, the use of sensors and sensor readings is significant in research and industry. The number of sensors is increasing exponentially, adding a tremendous amount of data to the Web. Therefore, the efficient management of sensors and observation data is becoming important. Especially, the location and time of observations are expected to play a vital role in IoT. However, existing researches mainly focus on the temporal properties of data stream. It is necessary to consider the spatial features in addition to the temporal ones. In this article, the authors propose a spatiotemporal query language which integrates spatial and temporal features. Also, they propose an efficient method of building a spatiotemporal index and processing the proposed query language. To evaluate the proposed method, the authors conduct experiments through implementation. The experimental results show that the proposed method deals with spatiotemporal queries within a reasonable time.

scholarly journals Prototype Sistem Monitoring Kekeruhan Sumber Mata Air Berbasis Internet of Things

2021 ◽  
Vol 2 (2) ◽  
pp. 66-72
Author(s):  
Udin ◽  
Heliawati Hamrul ◽  
Muh. Fuad Mansyur
Keyword(s):  
Internet Of Things ◽  
Water Level ◽  
Electric Current ◽  
Rainy Season ◽  
Query Language ◽  
Internet Access ◽  
Solenoid Valve ◽  
Water Turbidity ◽  
Living Things ◽  
Water Height

Water is very important for the life of living things on earth. The function of water for life cannot be replaced, but water taken directly from springs often experiences turbidity which usually occurs during the rainy season where excessive rainwater intensity can affect the clarity of the water flowing into people's homes. From this problem, it is necessary to design a monitoring sistem for the turbidity of water flowing into the main tank which can be monitored via laptops, computers or cellphones that have internet access that can monitor in real-time and in the form of graphs and data stored in My Structured Query language (mysql) in this design. Using the nodemcu esp8266 which controls the tool in the design, the turbidity sensor is used to detect water turbidity, the ultrasonic sensor is used to detect the water level in the main tank, the relay is used to control the electric current, the solenoid valve is used to close the valve according to the conditions given with the design results of 120 ntu down and water height > 15 cm then the on relay and solenoid valve open the valve so that water can flow into the reservoir, while 121 ntu up and water height < 5 cm then the off relay and solenoid valve close the valve, the test is done using blackbox testing and the results of this test that the function on the sistem is 100% appropriate.

scholarly journals A unified ontology-based data integration approach for the internet of things

2022 ◽  
Vol 12 (2) ◽  
pp. 2097
Author(s):  
Ahmed Swar ◽  
Ghada Khoriba ◽  
Mohamed Belal
Keyword(s):  
Internet Of Things ◽  
Data Integration ◽  
Query Language ◽  
Real Data ◽  
File Transfer ◽  
Standard Format ◽  
Ontology Model ◽  
Combining Data ◽  
Description Framework ◽  
And Performance

<span lang="EN-US">Data integration enables combining data from various data sources in a standard format. Internet of things (IoT) applications use ontology approaches to provide a machine-understandable conceptualization of a domain. We propose a unified ontology schema approach to solve all IoT integration problems at once. The data unification layer maps data from different formats to data patterns based on the unified ontology model. This paper proposes a middleware consisting of an ontology-based approach that collects data from different devices. IoT middleware requires an additional semantic layer for cloud-based IoT platforms to build a schema for data generated from diverse sources. We tested the proposed model on real data consisting of approximately 160,000 readings from various sources in different formats like CSV, JSON, raw data, and XML. The data were collected through the file transfer protocol (FTP) and generated 960,000 resource description framework (RDF) triples. We evaluated the proposed approach by running different queries on different machines on SPARQL protocol and RDF query language (SPARQL) endpoints to check query processing time, validation of integration, and performance of the unified ontology model. The average response time for query execution on generated RDF triples on the three servers were approximately 0.144 seconds, 0.070 seconds, 0.062 seconds, respectively.</span>

Incorporating Spatial Queries into Semantic Sensor Streams on the Internet of Things

2020 ◽  
pp. 1703-1719
Author(s):  
Sungkwang Eom ◽  
Kyong-Ho Lee
Keyword(s):  
Internet Of Things ◽  
Query Language ◽  
Vital Role ◽  
The Internet ◽  
Observation Data ◽  
Temporal Properties ◽  
Temporal Features ◽  
Tremendous Amount ◽  
Spatiotemporal Queries ◽  
The Internet Of Things

In the Internet of Things (IoT) environment, the use of sensors and sensor readings is significant in research and industry. The number of sensors is increasing exponentially, adding a tremendous amount of data to the Web. Therefore, the efficient management of sensors and observation data is becoming important. Especially, the location and time of observations are expected to play a vital role in IoT. However, existing researches mainly focus on the temporal properties of data stream. It is necessary to consider the spatial features in addition to the temporal ones. In this article, the authors propose a spatiotemporal query language which integrates spatial and temporal features. Also, they propose an efficient method of building a spatiotemporal index and processing the proposed query language. To evaluate the proposed method, the authors conduct experiments through implementation. The experimental results show that the proposed method deals with spatiotemporal queries within a reasonable time.

scholarly journals CTRUST: A Dynamic Trust Model for Collaborative Applications in the Internet of Things

2019 ◽  
Vol 6 (3) ◽  
pp. 5432-5445 ◽  
Author(s):  
Anuoluwapo A. Adewuyi ◽  
Hui Cheng ◽  
Qi Shi ◽  
Jiannong Cao ◽  
Aine MacDermott ◽  
...  
Keyword(s):  
Internet Of Things ◽  
Trust Model ◽  
The Internet ◽  
Dynamic Trust ◽  
Collaborative Applications ◽  
The Internet Of Things

scholarly journals Digital Twin and Internet of Things—Current Standards Landscape

2020 ◽  
Vol 10 (18) ◽  
pp. 6519 ◽  
Author(s):  
Michael Jacoby ◽  
Thomas Usländer
Keyword(s):  
Internet Of Things ◽  
Virtual Worlds ◽  
Industry 4.0 ◽  
Query Language ◽  
Building Blocks ◽  
Physical World ◽  
Cognitive Services ◽  
Digital Twins ◽  
Automate Production ◽  
The Internet Of Things

Industry 4.0 is revolutionizing industrial production by bridging the physical and the virtual worlds and further improving digitalization. Two essential building blocks in industry 4.0 are digital twins (DT) and the internet of things (IoT). While IoT is about connecting resources and collecting data about the physical world, DTs are the virtual representations of resources organizing and managing information and being tightly integrated with artificial intelligence, machine learning and cognitive services to further optimize and automate production. The concepts of DTs and IoT are overlapping when it comes to describing, discovering and accessing resources. Currently, there are multiple DT and IoT standards covering these overlapping aspects created by different organizations with different backgrounds and perspectives. With regard to interoperability, which is presumably the most important aspect of industry 4.0, this barrier needs to be overcome by consolidation of standards. The objective of this paper is to investigate current DT and IoT standards and provide insights to stimulate this consolidation. Overlapping aspects are identified and a classification scheme is created and applied to the standards. The results are compared, aspects with high similarity or divergence are identified and a proposal for stimulating consolidation is presented. Consensus between standards are found regarding the elements a resource should consist of and which serialization format(s) and network protocols to use. Controversial topics include which query language to use for discovery as well as if geo-spatial, temporal and historical data should be explicitly supported.

scholarly journals A oneM2M-Based Query Engine for Internet of Things (IoT) Data Streams

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3253 ◽  
Author(s):  
Putu Widya ◽  
Yoga Yustiawan ◽  
Joonho Kwon
Keyword(s):  
Internet Of Things ◽  
Query Processing ◽  
Data Streams ◽  
Query Language ◽  
Data Set ◽  
Real Time Processing ◽  
Network Bandwidth ◽  
Query Engine ◽  
Processing Algorithms ◽  
User Queries

The new standard oneM2M (one machine-to-machine) aims to standardize the architecture and protocols of Internet of Things (IoT) middleware for better interoperability. Although the standard seems promising, it lacks several features for efficiently searching and retrieving IoT data which satisfy users’ intentions. In this paper, we design and develop a oneM2M-based query engine, called OMQ, that provides a real-time processing over IoT data streams. For this purpose, we define a query language which enables users to retrieve IoT data from data sources using JavaScript Object Notation (JSON). We also propose efficient query processing algorithms which utilizes the oneM2M architecture consisting of two nodes: (1) the IoT node and (2) the infrastructure node. IoT nodes of OMQ are mainly sensor devices execute user queries the aggregate, transform and filter operators, whereas the infrastructure node handles the join operator of user queries. Since the query processing algorithms are implemented as the hybrid infrastructure-edge processing, user queries can be executed efficiently in each IoT node rather than only in the infrastructure node. Thus, our OMQ system reduces the query processing time and the network bandwidth. We conducted a comprehensive evaluation of OMQ using a real and a synthetic data set. Experimental results demonstrate the feasibility and efficiency of OMQ system for executing queries and transferring data from each IoT node.

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