scholarly journals A “Smart” Trap Device for Detection of Crawling Insects and Other Arthropods in Urban Environments

Electronics ◽  
2018 ◽  
Vol 7 (9) ◽  
pp. 161 ◽  
Author(s):  
Panagiotis Eliopoulos ◽  
Nikolaos-Alexandros Tatlas ◽  
Iraklis Rigakis ◽  
Ilyas Potamitis
Keyword(s):  
Insect Pests ◽  
Smart Cities ◽  
Urban Environments ◽  
Infrared Light ◽  
Internal Space ◽  
Detection Accuracy ◽  
Time Stamp ◽  
Military Camp ◽  
Urban Pests ◽  
The Internet Of Things

We introduce a device for the automatic detecting and reporting of crawling insects in urban environments. It is a monitoring device for urban pests that complies with the context of smart homes and smart cities, and is compatible with the emerging discipline of the Internet of Things (IoT). We believe it can find its place in every room of a hotel, hospital, military camp, and residence. This box-shaped device attracts targeted insect pests, senses the entering insect, and takes automatically a picture of the internal space of the box. The e-trap includes strong attractants (pheromone and/or food) to increase capture efficiency and traps the insect on its sticky floor. The device carries the necessary optoelectronic sensors to monitor all entrances of the trap. As the insect enters it interrupts the infrared light source. This triggers a detection event; a picture is taken, and a time-stamp is set before delivering the picture through the Wi-Fi to an authorized person/stakeholder. The device can be integrated seamlessly in urban environments and operates unobtrusively to human activities. We report results on various insect pests and depending on the insect species, can reach a detection accuracy ranging from 96 to 99%.

scholarly journals A “Smart” Trap Device for Detection of Crawling Insects and Other Arthropods in Urban Environments

2018 ◽  
Author(s):  
Panagiotis Eliopoulos ◽  
Nikolaos-Alexandros Tatlas ◽  
Iraklis Rigakis ◽  
Ilyas Potamitis
Keyword(s):  
Insect Pests ◽  
Smart Cities ◽  
Urban Environments ◽  
Infrared Light ◽  
Internal Space ◽  
Detection Accuracy ◽  
Proper Action ◽  
Military Camp ◽  
Urban Pests ◽  
The Internet Of Things

We introduce a device for automatic detection and reporting of crawling insects in urban environments. It is a monitoring device for urban pests that complies with the context of smart homes, smart cities and is compatible with the emerging discipline of the Internet of Things (IoT). We believe it can find its place to every room of a hotel, hospital, military camp and residence. This box-shaped device attracts targeted insect pests, senses the entering insect and takes automatically a picture of the internal space of the box. The picture is communicated through the Wi-Fi commonly found in such establishments to an authorized person/stakeholder receiving the picture to take proper action. The e-trap includes strong attractants (pheromone and/or food) to increase capture efficiency. The insect is trapped on the sticky floor of the device. The device carries the necessary optoelectronic sensors to guard all entrances of the trap. As the insect enters it interrupts the infrared light source. This triggers a detection event; a picture is taken, and a time-stamp is set before reporting the event through the Wi-Fi. The device can be integrated seamlessly in urban environments and operates unobtrusively to human activities. We report results on various insect pests and depending on the insect species, can reach a detection accuracy ranging from 96-99%.

scholarly journals A Novel Air Quality Monitoring Unit Using Cloudino and FIWARE Technologies

2019 ◽  
Vol 24 (1) ◽  
pp. 15
Author(s):  
Yolanda Baca Gómez ◽  
Hugo Estrada Esquivel ◽  
Alicia Martínez Rebollar ◽  
Daniel Villanueva Vásquez
Keyword(s):  
Quality Of Life ◽  
Air Quality ◽  
Smart Cities ◽  
Urban Environments ◽  
Quality Monitoring ◽  
Air Quality Monitoring ◽  
Factors Affecting ◽  
Industrial Societies ◽  
The Internet Of Things

Smart City applications aim to improve the quality of life of citizens. Applying technologies of the Internet of Things (IoT) to urban environments is considered as a key of the development of smart cities. In this context, air pollution is one of the most important factors affecting the quality of life and the health of the increasing urban population of industrial societies. For this reason, it is essential to develop applications that allow citizens monitoring the concentration of pollutants and avoid places with high levels of pollution. Due to the increasing use of IoT in different areas, there are arising platforms which deal with the challenges IoT implies, such as FIWARE, which provides technologies to facilitate the development of IoT applications. In this paper, an Air Quality Monitoring Unit using Cloudino and Arduino devices and FIWARE technologies is presented. Through Cloudino and Arduino, the monitoring unit gather data from various sensors and transforms the data in a FIWARE data model. Then, the measurements are sent to the Orion Context Broker (OCB), which is a software component provided by FIWARE. The Orion Context Broker allows to manage and publish the data to be consumed by users and applications.

scholarly journals Application of a Smart City Model to a Traditional University Campus with a Big Data Architecture: A Sustainable Smart Campus

2019 ◽  
Vol 11 (10) ◽  
pp. 2857 ◽  
Author(s):  
William Villegas-Ch ◽  
Xavier Palacios-Pacheco ◽  
Sergio Luján-Mora
Keyword(s):  
Big Data ◽  
Internet Of Things ◽  
Smart Cities ◽  
Urban Environments ◽  
Small Scale ◽  
The Internet ◽  
University Campus ◽  
Starting Point ◽  
High Investment ◽  
The Internet Of Things

Currently, the integration of technologies such as the Internet of Things and big data seeks to cover the needs of an increasingly demanding society that consumes more resources. The massification of these technologies fosters the transformation of cities into smart cities. Smart cities improve the comfort of people in areas such as security, mobility, energy consumption and so forth. However, this transformation requires a high investment in both socioeconomic and technical resources. To make the most of the resources, it is important to make prototypes capable of simulating urban environments and for the results to set the standard for implementation in real environments. The search for an environment that represents the socioeconomic organization of a city led us to consider universities as a perfect environment for small-scale testing. The proposal integrates these technologies in a traditional university campus, mainly through the acquisition of data through the Internet of Things, the centralization of data in proprietary infrastructure and the use of big data for the management and analysis of data. The mechanisms of distributed and multilevel analysis proposed here could be a powerful starting point to find a reliable and efficient solution for the implementation of an intelligent environment based on sustainability.

Security in Smart Healthcare System: A Comprehensive Survey

2017 ◽  
Vol 7 (10) ◽  
pp. 39
Author(s):  
P. Jeyadurga ◽  
S. Ebenezer Juliet ◽  
I. Joshua Selwyn ◽  
P. Sivanisha
Keyword(s):  
Secure Communication ◽  
Smart Cities ◽  
Healthcare Systems ◽  
Internet Security ◽  
Security Risk ◽  
System A ◽  
Smart Healthcare ◽  
Comprehensive Survey ◽  
Healthcare Monitoring ◽  
The Internet Of Things

The Internet of things (IoT) is one of the emerging technologies that brought revolution in many application domains such as smart cities, smart retails, healthcare monitoring and so on. As the physical objects are connected via internet, security risk may arise. This paper analyses the existing technologies and protocols that are designed by different authors to ensure the secure communication over internet. It additionally focuses on the advancement in healthcare systems while deploying IoT services.

scholarly journals Surveillance System in Smart Cities: A Dependability Evaluation Based on Stochastic Models

Electronics ◽  
2021 ◽  
Vol 10 (8) ◽  
pp. 876
Author(s):  
Igor Gonçalves ◽  
Laécio Rodrigues ◽  
Francisco Airton Silva ◽  
Tuan Anh Nguyen ◽  
Dugki Min ◽  
...  
Keyword(s):  
Surveillance System ◽  
Smart Cities ◽  
Heterogeneous Data ◽  
Time To Failure ◽  
Video Streams ◽  
Dependability Evaluation ◽  
The Mean ◽  
Mean Time ◽  
The Internet Of Things

Surveillance monitoring systems are highly necessary, aiming to prevent many social problems in smart cities. The internet of things (IoT) nowadays offers a variety of technologies to capture and process massive and heterogeneous data. Due to the fact that (i) advanced analyses of video streams are performed on powerful recording devices; while (ii) surveillance monitoring services require high availability levels in the way that the service must remain connected, for example, to a connection network that offers higher speed than conventional connections; and that (iii) the trust-worthy dependability of a surveillance system depends on various factors, it is not easy to identify which components/devices in a system architecture have the most impact on the dependability for a specific surveillance system in smart cities. In this paper, we developed stochastic Petri net models for a surveillance monitoring system with regard to varying several parameters to obtain the highest dependability. Two main metrics of interest in the dependability of a surveillance system including reliability and availability were analyzed in a comprehensive manner. The analysis results show that the variation in the number of long-term evolution (LTE)-based stations contributes to a number of nines (#9s) increase in availability. The obtained results show that the variation of the mean time to failure (MTTF) of surveillance cameras exposes a high impact on the reliability of the system. The findings of this work have the potential of assisting system architects in planning more optimized systems in this field based on the proposed models.

Robust Networking: Dynamic Topology Evolution Learning for Internet of Things

2021 ◽  
Vol 17 (3) ◽  
pp. 1-23
Author(s):  
Ning Chen ◽  
Tie Qiu ◽  
Mahmoud Daneshmand ◽  
Dapeng Oliver Wu
Keyword(s):  
Internet Of Things ◽  
Smart Cities ◽  
Evolutionary Process ◽  
Small Error ◽  
Cyber Attacks ◽  
Communication Capacity ◽  
Error Ratio ◽  
The Internet Of Things ◽  
Evolution Learning

The Internet of Things (IoT) has been extensively deployed in smart cities. However, with the expanding scale of networking, the failure of some nodes in the network severely affects the communication capacity of IoT applications. Therefore, researchers pay attention to improving communication capacity caused by network failures for applications that require high quality of services (QoS). Furthermore, the robustness of network topology is an important metric to measure the network communication capacity and the ability to resist the cyber-attacks induced by some failed nodes. While some algorithms have been proposed to enhance the robustness of IoT topologies, they are characterized by large computation overhead, and lacking a lightweight topology optimization model. To address this problem, we first propose a novel robustness optimization using evolution learning (ROEL) with a neural network. ROEL dynamically optimizes the IoT topology and intelligently prospects the robust degree in the process of evolutionary optimization. The experimental results demonstrate that ROEL can represent the evolutionary process of IoT topologies, and the prediction accuracy of network robustness is satisfactory with a small error ratio. Our algorithm has a better tolerance capacity in terms of resistance to random attacks and malicious attacks compared with other algorithms.

scholarly journals Distant Measurement of Plethysmographic Signal in Various Lighting Conditions Using Configurable Frame-Rate Camera

2016 ◽  
Vol 23 (4) ◽  
pp. 579-592 ◽  
Author(s):  
Jaromir Przybyło ◽  
Eliasz Kańtoch ◽  
Mirosław Jabłoński ◽  
Piotr Augustyniak
Keyword(s):  
Heart Rate ◽  
Assisted Living ◽  
Detection Algorithm ◽  
Frame Rate ◽  
Infrared Light ◽  
Fluorescent Light ◽  
Detection Accuracy ◽  
Rate Measurement ◽  
Lighting Conditions ◽  
Heart Rate Measurement

Abstract Videoplethysmography is currently recognized as a promising noninvasive heart rate measurement method advantageous for ubiquitous monitoring of humans in natural living conditions. Although the method is considered for application in several areas including telemedicine, sports and assisted living, its dependence on lighting conditions and camera performance is still not investigated enough. In this paper we report on research of various image acquisition aspects including the lighting spectrum, frame rate and compression. In the experimental part, we recorded five video sequences in various lighting conditions (fluorescent artificial light, dim daylight, infrared light, incandescent light bulb) using a programmable frame rate camera and a pulse oximeter as the reference. For a video sequence-based heart rate measurement we implemented a pulse detection algorithm based on the power spectral density, estimated using Welch’s technique. The results showed that lighting conditions and selected video camera settings including compression and the sampling frequency influence the heart rate detection accuracy. The average heart rate error also varies from 0.35 beats per minute (bpm) for fluorescent light to 6.6 bpm for dim daylight.

Design and Analysis of a RFID Reader Microstrip Array antenna for IoT Applications in Smart Cities

2022 ◽  
Vol 17 (5) ◽  
pp. 0-0
Keyword(s):  
Smart Cities ◽  
Array Antenna ◽  
The Internet ◽  
Substrate Thickness ◽  
Iot Applications ◽  
Rfid Reader ◽  
Array Antennas ◽  
Microstrip Array ◽  
The Internet Of Things ◽  
Microstrip Array Antenna

This paper presents the design of 2*1 and 4*1 RFID reader microstrip array antenna at 2.4GHz for the Internet of things (IoT) networks which are Zigbee, Bluetooth and WIFI. The proposed antenna is composed of identical circular shapes radiating patches printed in FR4 substrate. The dielectric constant εr and substrate thickness h are 4.4 and 1.6mm, respectively. The 2*1 and 4*1 array antennas present a gain improvement of 27.3% and 61.9%, respectively. The single,2*1 and 4*1 array antennas were performed with CADFEKO.

The Internet of Things: Making Cities — AndThe Way They Use Technology — Smarter

2016 ◽  
Author(s):  
Wendy W. Fok ◽  
Keyword(s):  
New York ◽  
Internet Of Things ◽  
Energy Use ◽  
Smart Cities ◽  
Traffic Monitoring ◽  
Urban Life ◽  
The Internet ◽  
Time Data ◽  
Heating And Cooling ◽  
The Internet Of Things

Minerva Tantoco was named New York City’s first chief technology officer last year, charged with developing a coordinated citywide strategy on technology and innovation. We’re likely to see more of that as cities around the country, and around the world, consider how best to use innovation and technology to operate as “smart cities.”The work has major implications for energy use and sustainability, as cities take advantage of available, real-time data – from ‘smart’ phones, computers, traffic monitoring, and even weather patterns — to shift the way in which heating and cooling systems, landscaping, flow of people through cities, and other pieces of urban life are controlled. But harnessing Open Innovation and the Internet of Things can promote sustainability on a much broader and deeper scale. The question is, how do you use all the available data to create a more environmentally sound future? The term “Internet of Things” was coined in 1999 by Kevin Ashton, who at the time was a brand manager trying to find a better way to track inventory. His idea? Put a microchip on the packaging to let stores know what was on the shelves.

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