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Toward ubiquitous mobility solutions for body sensor networks on healthcare
Body sensor networks (BSN) appeared as an
application of Wireless Sensor Networks (WSN) to medicine
and biofeedback. Such networks feature smart sensors
(biosensors) that capture bio-physiological parameters from
people and can offer an easy way for data collection. BSNs
also need suitable interfaces for data processing, presentation,
and storage for latter retrieval. As a result, Bluetooth
technology can be used to communicate with several more
powerful and graphical user interface (GUI)-enabled devices
such as mobile phones or regular computers. Taking into
account that people currently use mobile and smart phones, it
offers a good opportunity to propose a suitable mobile system
for BSN networks. This paper presents a BSN mobile solution
for biofeedback monitoring using the four major smart phone
platforms: Symbian, Windows Mobile, Android, and iPhone.
As case study, a sensing health with intelligence modularity,
mobility and experimental reusability (SHIMMER) platform
with a core-body temperature sensor enabled to construct the
BSN was used. The four mobile applications were evaluated
and validated, and are ready for use.
Increasing demand of mobile applications for on-site data acquisition pushes the development of flexible and easy to use mobile tools, with great advantages over the traditional computer-based approaches. The Accept System from SINMETRO allows data gathering for quality control, in the form of Inspection sheets. Such tool allows quality assurance by monitoring some samples of a given material, for instance milk, wine, and even maintenance management.
This paper presents a mobile application in the Accept System that allows a Personal Digital Assistant (PDA) device to perform data gathering based on XML Inspection templates. Using .NET Compact Framework through C#, and database the technologies SQL Server and SQL Server CE, we developed Accept Mobile.
Accept Mobile uses the Remote Data Access (RDA) mechanism to send data over to the server through a synchronization service, while also providing the needed support for disconnected operation. We prove that the mobile application is very convenient and provides enough functionality for the user to dismiss the portable computer, although the main application was never developed with mobility concerns in mind.
A Body Sensor Network can sense health parameters directly on the patient’s body, allowing 24/7 monitoring in an unobtrusive way. Several tiny sensors collect and route data to a special sink node. A new intra-vaginal biosensor was developed to study the relation between temperature variations and women health conditions, such as ovulation period, among others. We present a biosensor prototype and some initial results on real scenarios with a woman. One of the main issues in a body sensor network is the transformation of the sensor raw data into meaningful medical data for medical staff. Several approaches exist, from mobile device-based approaches to more powerful hardware such as a personal computer. This paper presents our current work in body sensor networks, namely a prototype for intra-vaginal temperature monitoring with initial results, and a mobile tool for data presentation of a three-tier body sensor network. The gathered results demonstrate the feasibility of the approach, contributing to the widespread application of body sensor networks.
Over the years some medical studies have tried to better understand the internal
behavior of human beings. Many researchers in this domain have been striving to find
relationships between intra-vaginal temperature and certain female health conditions, such
as ovulation and fertile period since woman’s intra-vaginal temperature is one of the body
parameters most preferred in such studies. However, due to lack of a appropriate
technology, medical research devoted to studying correlations of such body parameters
with certain womans’ body phenomena could not obtain better results. This article presents
the design and implementation of a novel intra-body sensor for acquisition and monitoring
of intra-vaginal temperatures. This novel intra-body sensor provides data collection that is
used for studying the relation between temperature variations and female health conditions,
such as anticipation and monitoring of the ovulation period, detection of pregnancy
contractions, preterm labor prevention, etc.. The motivation for this work focuses on the
development of this new intra-body sensor that will represent a major step in medical
technology. The novel sensor was tested and validated on hospitalized women as well as
normal healthy women. Finally our medical team has attested to the accuracy, usability and
performance of this novel intra-body sensor.
The conjugation of small nodes with sensing, communication and processing capabilities allows for the creation of wireless sensor networks (WSNs). These networks can be deployed to measure a very wide range of environmental phenomena and send data from remote locations back to users. They offer new and exciting possibilities for applications and research. This paper presents the background of WSNs by firstly exploring the different fields applications, with examples for each of these fields, then the challenges faced by these networks in areas such as energy-efficiency, node localization, node deployment, limited storage and routing. It aims at explaining each issue and giving solutions that have been proposed in the research literature. Finally, the paper proposes a practical scenario of deploying a WSN by autonomous robot path construction. The requirements for such a scenario and the open issues that can be tackled by it are exposed, namely the issues of associated with measuring RSSI, the degree of autonomy of the robot and connectivity restoration.
“© © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”
O trabalho apresentado no contexto deste artigo pretende contribuir para a construção de uma rede sem fios composta por vários pontos de acesso móveis com a capacidade de se organizarem autonomamente de modo a cobri- rem uma área definida. Nesse sentido, apresenta o desenho, implementação e avaliação de desempenho de um algoritmo que coordena a deslocação autóno- ma de um robô até um nó de destino, com base na avaliação do parâmetro Re- ceived Signal Strength Indication.
The use of wireless sensor networks (WSN) can be a valuable contribution in disaster situations or life-threatening exploration. Using wireless mobile robots, it is possible to explore vast areas without human intervention. However, the wireless network coverage that can keep mobile robots connected to the base station / gateway is a major limitation. With this in mind it was created a prototype of an extensible WSN using mobile robot nodes that cooperate amongst themselves. The strategy adopted in this project proposes using three types of nodes: master node, static node, and robot node. Three different algorithms were also developed and proposed: Received Signal Strength Indication (RSSI) Request; Automovement; Robot Cooperation and Response to Static Node. The performance evaluation of the prototype was carried out using a real-world testbed with each developed algorithm. The results achieved were very promising to continue the evolution of the prototype.
This paper presents a wireless mesh network testbed based on ESP8266 devices using painlessMesh library. It evaluates its feasibility and potential effectiveness as a solution to monitor perishable goods, such as fresh fruit and vegetables, which are often stored and transported inside refrigerated containers. Performance testing experiments with different numbers of nodes and traffic loads and different message payload sizes are conducted under unicast transmission. The impact on network performance is evaluated in terms of delivery ratio and delivery delay, which, consequently, affect the energy consumption and, hence, network lifetime. The results of this investigation are an important contribution to help researchers to propose mechanisms, schemes, and protocols to improve performance in such challenging networks.
Climacteric fruit such as peaches are stored in cold chambers after harvest and usually are maintained there until the desired ripening is reached to direct these fruit to market. Producers, food industries and or traders have difficulties in defining the period when fruit are at the highest level of quality desired by consumers in terms of the physical-chemical parameters (hardness –H–, soluble solids content –SSC–, and acidity –Ac–). The evolution of peach quality in terms of these parameters depends directly on storage temperature –T– and relative humidity –RH–, as well on the storage duration –t–. This paper describes an Artificial Intelligence (AI) Decision Support System (DSS) designed to predict the evolution of the quality of peaches, namely the storage time required before commercialization as well as the late commercialization time. The peaches quality is stated in terms of the values of SSC, H and Ac that consumers most like for the storage T and RH. An Artificial neuronal network (ANN) is proposed to provide this prediction. The training and validation of the ANN were conducted with experimental data acquired in three different farmers’ cold storage facilities. A user interface was developed to provide an expedited and simple prediction of the marketable time of peaches, considering the storage temperature, relative humidity, and initial physical and chemical parameters. This AI DSS may help the vegetable sector (logistics and retailers), especially smaller neighborhood grocery stores, define the marketable period of fruit. It will contribute with advantages and benefits for all parties—producers, traders, retailers, and consumers—by being able to provide fruit at the highest quality and reducing waste in the process. In this sense, the ANN DSS proposed in this study contributes to new AI-based solutions for smart cities.
Wireless Body Sensors for medical purposes offer valuable contributions to improve patients’ healthcare, including diagnosis and/or therapeutics monitoring. Body temperature is a crucial parameter in healthcare diagnosis. In gynecology and obstetrics it is measured at the skin’s surface, which is very influenced by the environment. This paper proposes a new intra-body sensor for long-term intra-vaginal temperature collection. The embedded IEEE 802.15.4 communication module allows the integration of this sensor in a Wireless Sensor Network (WSN) for remote data access and monitoring. We present the sensor architecture, the construction of the corresponding testbed, and its performance evaluation. This sensor may be used in different medical applications, including preterm labor prevention and fertility and ovulation period detection. The features of the constructed testbed were validated in laboratory tests verifying its accuracy and performance.
“Copyright © [2010] IEEE. Reprinted from 2nd International Conference on eHealth, Telemedicine, and Social Medicine . ISBN: 978-0-7695-3950-8. This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.”
Copyright © [2010] IEEE. Reprinted from 12th IEEE International Conference on e-Health Networking, Applications and Services . ISBN: 978-1-4244-6374-9. This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.”
“Copyright © [2011] IEEE. Reprinted from Internet of Things (iThings/CPSCom), 2011 International Conference on and 4th International Conference on Cyber, Physical and Social Computing. ISBN 978-1-4577-1976-9
This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org. By choosing to view this document, you agree to all provisions of the copyright laws protecting it.”
The detection of fertile and ovulation periods may
be performed by women’s body temperature variations. These
variations are more accurate if a core-body temperature for
their detection is used. Previous medical studies concluded that
the use of skin temperature could be influenced by
environmental conditions. Since the increasing of the body
temperature in this period is only about 0.5 ºC, it is crucial that
measurements should be the most accurate as possible. Due to
the lack of solutions to realize that in order to measure and
analyze the core-body temperature, this paper presents a
system to capture, display, and monitoring core-body
temperature. It is considered a hardware solution (sensor) to be
placed inside cervix and a computer application to
communicate and gather the collected data by the sensor.
Bluetooth is used to perform the communication between a
computer and the sensor. The system evaluation is performed
by a medical team in several volunteer women. Furthermore,
the collected data by the sensor may be used to study the
relation between temperature variations and women health
conditions.
Recently, Google launched the Android mobile operating system
and several mobile devices already support it. This paper
proposes a mobile Android-enabled tool for collecting,
monitoring, and analyzing intra-vaginal temperature. A previous
proposed intra-vaginal sensor acquires temperature values and
sends the collected data to Android device over a Bluetooth
connection. The Android tool allows women for real-time
monitoring of their temperature with mobility support and
following their daily life. Woman can control and detect their
fertile and ovulation periods when this human parameter
increases about 0.5ºC over their regular temperature. Other
application of this solution includes the preterm labor
prevention. The proposed system was evaluated and validated,
and it is ready for use.
Sensor nodes are small devices able to collect and retrieve
sensorial data. The use of these sensors for medical purposes
offers valuable contributions to improve patients’ healthcare, both
for diagnosis and therapeutics monitoring. An important and
common parameter used on healthcare diagnosis is the body
temperature. It is monitored on several matters related with
gynecological and obstetrics issues but, usually it is measure at
the skin surface. Then, this paper proposes the design concepts of
a new intra-body sensor for long-term intra-vaginal temperature
collection. The embedded IEEE 802.15.4 communication module
allows the integration of this sensor in wireless sensor networks
for remote data access and monitoring. It is presented the sensor
architecture, the construction of the corresponding testbed, and its
performance evaluation. This sensor may be used on several
applications, including fertile and ovulation period detection, and
preterm labor prevention.
A aplicação de novas contribuições científicas para a
análise de processos fisiológicos deu origem a uma nova era na
medicina, introduzindo técnicas e dispositivos para medição e
monitorização de parâmetros fisiológicos. Este trabalho tem
como objectivo a apresentação de um novo sensor de
temperatura para medição e monitorização da temperatura
intra-vaginal. Esta monitorização irá permitir estudar as
variações deste parâmetro biológico ao longo de determinado
período de tempo, como por exemplo, ao longo de todo um ciclo
menstrual ou durante um dos dias desse ciclo. O conhecimento do
comportamento deste parâmetro biológico poderá ser
extremamente útil do ponto de vista clínico. Com base nesse
conhecimento e nas suas correlações com determinados estados
sintomáticos da fisiologia feminina, poderá ser possível estudar e
propor novos métodos para combater a infertilidade dos casais,
antecipar e monitorizar o período fértil (podendo ser usado, tanto
para ajudar a favorecer a gravidez como apoio a métodos de
anti-concepção), propor e ajustar terapêuticas de tratamento de
inúmeras doenças ginecológicas, desenvolver novos métodos
anti-concepcionais e ajuda à prevenção de partos pré-termo. O
protótipo do sistema foi testado e validado com sucesso, estando
pronto para utilização.
“Copyright © 2018 IEEE. Reprinted from 13th Iberian Conference on Information Systems and Technologies (CISTI). ISBN: 978-989-98434-8-6.
This material is posted here with permission of the IEEE. Internal or personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution must be obtained from the IEEE by writing to pubs-permissions@ieee.org.By choosing to view this document, you agree to all provisions of the copyright laws protecting it.”
The idea of monitoring several types of parameters in various environments has been motivating significant research works in Internet of Things (IoT). This paper presents the design and construction of iSensA, a system for integrating and collecting information from sensors. The solution implements a multi-sensor monitoring system and then expands the monitoring concept to an IoT solution, by employing multi-network access, Web services, database and web and mobile applications for user interaction. iSensA system is highly configurable, enabling several monitoring solutions with different types of sensors. Experiments have been performed on real application scenarios to validate and evaluate our proposition.
This work is a part of an ongoing study to substitute the identification of waste containers via radio-frequency identification. The purpose of this paper is to propose a method of identification based on computer vision that performs detection using images, video, or real-time video capture to identify different types of waste containers. Compared to the current method of identification, this approach is more agile and does not require as many resources. Two approaches are employed, one using feature detectors/descriptors and other using convolutional neural networks. The former used a vector of locally aggregated descriptors (VLAD); however, it failed to accomplish what was desired. The latter used you only look once (YOLO), a convolutional neural network, and reached an accuracy in the range of 90%, meaning that it correctly identified and classified 90% of the pictures used on the test set.
This paper presents a new approach to help redesigning waste management for the cities of the future. The current state of tracking waste containers is rigid, inefficient and hard to oversee. Although attempts have been made in the past using radio-frequency identification for waste container detection, it has shown problems like flexibility, cost and environmental impact. We propose and demonstrate a solution based on the use of computer vision techniques, for object detection and classification, towards the differentiation between different types of waste containers.
Este artigo apresenta o desenho e implementação de um protótipo fun- cional para avaliar e validar a utilização de técnicas de visão computacional, na identificação de contentores de resíduos no contexto de uma cidade inteligente. Este protótipo recorre à utilização de uma rede neuronal convolucional YOLO e de um microcomputador Jetson Nano da Nvidia. Comparativamente ao método atual de identificação de contentores de resíduos por radiofrequência, esta abor- dagem é mais ágil e diminui os recursos necessários para implementação, contri- buindo para poupar nos gastos logísticos e de implementação da gestão inteli- gente de resíduos.
O trabalho apresentado resulta de uma investigação preliminar que
visa a utilização de técnicas de visão computacional para substituir
o método atual de identificação de contentores de resíduos via
identificação por radiofrequência.
Comparativamente ao método atual, esta abordagem é mais ágil e
diminui os recursos necessários para implementação. A abordagem
aqui discutida é centrada no uso de redes neuronais convolucionais,
mais especificamente a rede YOLO.
The agro-industrial sector consumes a significant amount of natural resources for farming and meat production. By 2050, population growth is expected, generating more demand and, consequently, more consumption of scarce resources. This challenging scenario is a concern of the European Commission, revealed in the Green Deal commitment and by the United Nations’ 12th goal of sustainable development. Thus, organizations must increase productivity and be more sustainable as soon as possible. Internet of Things (IoT) is introduced as a solution to facilitate agro-food companies to be more eco-efficient, mainly facing difficulties on farms, such as food loss and waste, best efficiency in management of resources, and production. The deployment of this technology depends on the stage of maturity and potential of implementation. To assess and characterize companies, with respect of IoT implementation, a survey was applied in 21 micro, small and medium agro-food companies, belonging to milk, honey, olive oil, jams, fruticulture, bakery and pastry, meat, coffee, and wine sectors, in the central region of Portugal. As results, this paper reveals the stage of maturity, level of sophistication, potential, opportunities, solutions, and barriers for implementation of IoT. Additionally, suggestions and recommendations to improve practices are discussed.
Este artigo apresenta o desenho e implementação de um protótipo para a empresa EVOX Technologies, para obtenção de informação sobre níveis de enchimento, anomalias e outros alertas relacionados com contentores de resíduos urbanos, aquando da recolha destes pelos cantoneiros. São descritas as tecnologias adotadas a nível de hardware e software para implementação do protótipo baseado num LCD que comunica com um sistema de gestão de resíduos. Constitui uma alternativa viável e vantajosa à solução tradicional baseada numa botoneira simples e estática, contribuindo para a gestão em tempo real e para a redução dos gastos logísticos e de implementação da gestão inteligente de resíduos.
Smart lockers are intelligent storage units that are increasingly being adopted to help solving the last mile problem. This paper focuses on the concept of an individual smart locker that can be installed at the entrance of a residential house. First, the operational principle and advantages of this concept are discussed. Then, the design, development and implementation of a functional prototype is demonstrated. The prototype was submitted to tests and can be used as a proof of concept.
This paper presents the performance evaluation of a wireless sensor mesh network, for monitoring temperature and humidity in horticultural products when transported in truck galleys. For this purpose a software solution was proposed using ESP8266 devices powered by batteries. The mesh network was managed by the painlessMesh library. The proposed solution aims to minimize the energy consumption of the sensor nodes. The validation of the solution was performed in an area simulating a galley of a truck, where five sensor nodes and a root node were distributed. The tests were developed considering four different models involving variations in messages delivery confirmation, number of attempts until successful delivery and duty cycle duration of the nodes. The performance evaluation of the solution aimed to determine, connectivity rate, sending rate after connection and delivery rates of the first and second attempts. The results obtained show that the message delivery confirmation does not bring added value to the solution, contributing only to increase energy consumption. The use of synchronous duty cycles also showed worse results than the asynchronous use. These results allow the creation of a knowledge base for the use of this solution in a real context.
Wireless sensor networks are an emerging technology that is used to monitor points or objects of interest in an area. Despite its many applications, this kind of network is often limited by the fact that it is difficult to provide energy to the nodes continuously, forcing the use of batteries, which restricts its operations. Network density may also lead to other problems. Sparse networks require stronger transmissions and have little redundancy while dense networks increase the chances of overhearing and interference. To address these problems, many novel medium access control (MAC) protocols have been developed through the years. The objective of this study is to assess the effectiveness of the T-MAC, B-MAC, and RI-MAC protocols in a variable density network used to collect data inside freight trucks carrying fruits that perish quickly. This article is part of the PrunusPós project, which aims to increase the efficiency of peach and cherry farming in Portugal. The comparison was done using the OMNET++ simulation framework. Our analysis covers the behavior and energetic properties of these protocols as the density of the network increases and shows that RI-MAC is more adaptable and consumes less energy than the alternatives.
Vehicular networks are emerging as a promising technology that enables reliable and low-cost solutions for intelligent transport systems (ITSs), mainly due to their enormous potential to be considered for multiple purposes and scenarios. These networks are characterized by unique and challenging features such as packet fragmentation, low node density, short contact duration, and network disruption. These features may result in the absence of a path between the source and destination nodes, which is one of the most challenging issues faced by this type of network. To overcome some of these problems, it is necessary to provide vehicular networks with sophisticated tools or methodologies to implement monitoring and management operations. However, designing efficient solutions for this type of network is not an easy task due to its particular characteristics. This paper elaborates on a comprehensive survey focusing on promising proposals to deal with monitoring and management functionalities in vehicular networks. This work aims not only to present the state of the art on monitoring and management solutions but also to analyze their benefits and drawbacks, identify open issues, and provide guidelines for further contributions.
