In this study, we focus on the problem of managing a hybrid, shared IoT-based monitoring system, in which stationary sensor devices are complemented with user-carried personal devices embedded with sensing capabilitie...
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ISBN:
(纸本)9781728169972
In this study, we focus on the problem of managing a hybrid, shared IoT-based monitoring system, in which stationary sensor devices are complemented with user-carried personal devices embedded with sensing capabilities. The envisioned crowd-assisted monitoring system must support the sharing of the sensing infrastructure among multiple concurrent sensing tasks that can have highly varying QoS requirements. In such a scenario, a key issue is to maximise the utilisation efficiency of the physical sensing resources and the QoS satisfaction of sensing tasks while limiting the redundancy of collected data. As in previous research, we advocate the use of an IoT Broker, an intermediary entity that (i) interacts with the IoT applications to collect their QoS requirements (i.e., spatial coverage, data notification frequency);and (ii) coordinates with the redundant sensor deployments and mobile devices to selectively activate and configure the data streams that are needed to fulfil application requirements in a cost-efficient way. Then, we have developed an optimisation framework to jointly select the set of physical sensing resources to activate and the data update frequency for maximising the overall sensing performance while limiting redundant data. A key feature of our proposed framework is to be privacy-friendly as it only requires coarse-grained space-time knowledge of device location. Extensive simulations under realistic WSN deployments and real-life mobility patterns confirm the efficiency of the proposed solution in terms of data-coverage gain and reduction of data redundancy with respect to classical non-hybrid monitoring systems.
As the age profile of various societies keeps going up all over the world, in addition to the continuous surge in the populace suffering from long term illnesses, including diabetes, hypertension, cardiovascular probl...
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Dry type air core reactor is often operated outdoors, and its insulation performance is affected by climate, insulation aging, voltage fluctuation and other factors, which makes it encounter various problems in operat...
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This research presents the design and control of an automatic monitoring system of the main water parameters for rainbow trout culture, which is a freshwater species distributed in the high Andean zones along with the...
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ISBN:
(纸本)9781665406918
This research presents the design and control of an automatic monitoring system of the main water parameters for rainbow trout culture, which is a freshwater species distributed in the high Andean zones along with the Andes mountain range, which will be given through mechatronic systems. This work presents the control and monitoring of temperature, dissolved oxygen level, pH, and water level independently so that monitoring and control are simple. The procedure shows the use of different sensors that capture the water parameters such as the use of a Ceratex analog sensor to measure the pH, also the PT100 that will help us to calculate the temperature, and finally an Oxymax sensor for dissolved oxygen, all this helps us to extend the species and prevent its extinction, For the part of the programmed environment the information will be sent and displayed in the visual environment of the system, parallel to this the controller will act based on the information received, to maintain the water parameters in the appropriate range for rainbow trout, which are dissolved oxygen greater than 6 mg / l and less than 8. 5mg/l, within the temperature level, the species lives in waters of 9° to 14° C and with a pH of 6.6 to 7.9. In addition, the automatic mechatronic system implemented will facilitate and improve the monitoring and control of water parameters for rainbow trout culture.
This paper presents a scalable open source IoT architecture. The proposed sensor network transforms a bicycle into a mobility way that records, stores and displays information acquired from multiple integrated sensors...
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ISBN:
(纸本)9783030222635;9783030222628
This paper presents a scalable open source IoT architecture. The proposed sensor network transforms a bicycle into a mobility way that records, stores and displays information acquired from multiple integrated sensors, such as body sensors, bicycle sensors, ambient sensors, and smartphones. The system uses a Raspberry Pi 3 as a storage server and Broker MQTT interconnecting different nodes that collect measurements of bicycle distance/speed, ambient temperature and humidity, measurements of accelerations and angular velocities in the three axes. This architecture is configured as an access point connected through ieee 802.11 using MQTT as a communication protocol. The information obtained is stored in a database using SQLite and displayed in real time on a smartphone, tablet or computer. Our prototype incorporates changes in the previously proposed architecture by improving the connection of new sensor nodes by modifying the access point and integrating the sensor node of temperature and humidity into the network.
Dry-type air-core reactor widely used in power systems is affected by many factors such as the manufacturing process, operating environment, insulation aging. The insulation performance has deteriorated, resulting in ...
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Modern society is heavily reliant on information and communication technologies, which has made it more vulnerable to a wide range of cyber-attacks in recent decades. A distributed Denial-of-Service (DDOS) attack, for...
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ISBN:
(纸本)9781665447539
Modern society is heavily reliant on information and communication technologies, which has made it more vulnerable to a wide range of cyber-attacks in recent decades. A distributed Denial-of-Service (DDOS) attack, for example, uses the strength of hundreds or even thousands of infected computer systems to attack data-processing services and online businesses sites, increasing as a result disruption and financial losses, and therefore denying services to legitimate customers. The study of distributed denial-of-service attacks is an important area of research which has been addressed by various approaches. In this review, we are mainly focusing on AI methods namely, Bayesian networks, K-nearest neighbor algorithm, fuzzy logic, Neural Network, Support Vector Machine, and Genetic Algorithm to address distributed denial-of-service attacks.
IoT is a revolutionary technology that represents the future of computing and communications. The paper focuses on the characterization of a Wireless sensor Network used for smart agriculture, which is one of the new ...
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ISBN:
(纸本)9781728144610;9781728144603
IoT is a revolutionary technology that represents the future of computing and communications. The paper focuses on the characterization of a Wireless sensor Network used for smart agriculture, which is one of the new frontiers of IoT. Smart farming is the application of information and data technologies for optimizing complex farming systems. WSNs are widely used to measure agri-related information like temperature, humidity, solar radiation, presence of pollution and so on. In this paper the design of a wireless mesh network composed by low cost and low power system-on-a-chip is presented dealing with the frequently encountered issues of wireless networks. In particular, this work proposes a framework for the characterization of customized devices designed for monitoring networks: different types of test are performed in order to analyze the behavior of the components. The work focuses on the maximum coverage distance which is a critical parameter in agriculture field since the largeness of the involved area;it also deals with the thermal characterization to improve reliability performances and ADC calibration to ensure high accuracy of the acquired data. Moreover, the paper pays great attention on the power consumption of the sensor node, in fact the minimization of the current consumption of the nodes is a mandatory requirement to ensure low maintenance costs.
During a criminal investigation, the evidence collection process produces an enormous amount of data. These data are present in many medias that are extracted as crime evidences (USB flash drives, smartphones, hard dr...
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ISBN:
(纸本)9781728170220
During a criminal investigation, the evidence collection process produces an enormous amount of data. These data are present in many medias that are extracted as crime evidences (USB flash drives, smartphones, hard drives, computers, etc). Due to this data volume, the manual analysis is slow and costly. This work fulfills this gap by presenting a data extraction and processing platform for crime evidence analysis, named INSIDE. Our proposed platform leverages a lambda architecture and uses a set of tools and frameworks such as Hadoop HDFS, Kafka, Spark and Docker to analyze a big volume of data at an acceptable time. We also present an example of the proposed platform in use by the Public Ministry of Rio Grande do Norte(Brazil), where some evaluative tests have been carried out.
At present, one of the main issues of interest is climate change. It triggers calamitous phenomena (fires, hydrogeological instability and many others) that put crops, vegetation and even human beings at risk. Conside...
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ISBN:
(纸本)9781665426060
At present, one of the main issues of interest is climate change. It triggers calamitous phenomena (fires, hydrogeological instability and many others) that put crops, vegetation and even human beings at risk. Considering the phenomenon of hydrogeological instability, there is a wide range of smart application contexts (for example, smart city, smart road and smart agriculture), which require a real-time rainfall level monitoring, recognition and classification system. This system is supposed to provide accurate and real-time estimates of rain intensity and alert those in charge in order to reduce the risks associated with the various application contexts. Thus, the present paper proposes an audio sensor enabled real-time audio rainfall classification, based on 1-D convolutional neural network (CNN) which offers 95% classification accuracy in five rainfall intensity classes.
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