GR-40 Design and Implementation of a Microservices Web-based Architecture for Code Deployment and Testing

Many tech stars like Netflix, Amazon, PayPal, eBay, and Twitter are evolving from monolithic to a microservice architecture due to the benefits for Agile and DevOps teams. Microservices architecture can be applied to multiple industries, like IoT, using containerization. Virtual containers give an ideal environment for developing and testing IoT technologies. Since the IoT industry has exponential growth, it is the responsibility of universities to teach IoT with hands-on labs to minimize the gap between what the students learn and what is on-demand in the job market. That can be done by using containerization. There are many approaches in the containerization field, but they can be difficult to use without depth knowledge in virtualization and code encapsulation. After a deep analysis of the containerization challenges, we came with an idea of a microservice infrastructure based on Docker, which is an open- platform for developing, testing, and running applications using containers, to solve the virtualization and code-encapsulation problem. Our infrastructure will provide a code development and testing web-based platform that allows users to securely go in the process of containerization without spending research time in learning virtualization. So, students and researchers can focus more on the development and testing of algorithms and codes. For example, it will be easy to develop containers that allow sensors to connect to an external server in few cliques, or to run a python code in a total isolate process in minutes without downloading any containerization software.Advisors(s): Dr. Maria Valero [email protected] Dr Hossain Shahriar [email protected](s): IoT/Cloud/Networkin

Attitudes of women and men towards contraception in Bobo-Dioulasso

The extent of knowledge and practice of contraception in African populations remains hard to evaluate and despite the great influx of data from the World Fertility Surveys, the impact of contraception on fertility levels is difficult to measure. The practice of abstinence for the purpose of spacing births is widespread in Africa. It was discussed in demographic terms already by Lorimer in 1954. More recently the Caldwells (1977, 1981), by carefully investigating the phenomenon among the Yoruba, contributed greatly to establish the place of sexual abstinence in the study of the determinants of African fertility. Lately, data from the World Fertility Survey have shown large variations in the length of post-partum abstinence between countries and among different ethnic groups. Anthropological research has thrown some light on the different functions attributed to post-partum sexual abstinence, and the different reasons for practicing it

Secure Cloud-based IoT Water Quality Gathering for Analysis and Visualization

Water quality refers to measurable water characteristics, including chemical, biological, physical, and radiological characteristics usually relative to human needs. Dumping waste and untreated sewage are the reasons for water pollution and several diseases to the living hood. The quality of water can also have a significant impact on animals and plant ecosystems. Therefore, keeping track of water quality is a substantial national interest. Much research has been done for measuring water quality using sensors to prevent water pollution. In summary, those systems are built based on online and reagent-free water monitoring SCADA systems in wired networks. However, centralized servers, transmission protocols, and data access can present challenges and disadvantages for those systems. This paper proposes a secure Cloud-based IoT water quality gathering architecture for water quality analysis and visualization to address the limitations of the current systems. The proposed architecture will send, analyze and visualize water quality data in the Cloud by utilizing specialized sensors and IoT-based gateways to capture water measurements (Dioxygen concentration, and temperature, among others). Then, they communicate securely to the Cloud-based server through a high-speed wireless network. We evaluated the performance of the proposed framework on a process-oriented approach to success metrics for cyberinfrastructures. The experiments were conducted in a laboratory and focused on network security and resiliency, the IoT prototype performance in dropping real-time data transmission, and remote access. The results demonstrate higher data collection and transmission effectiveness with minimal data loss and low energy usage over time. The accompanying cloud-based platform provided the flexibility needed for water quality monitoring and laboratory studies

IoT Clusters Platform for Data Collection, Analysis, and Visualization Use Case

Climate change is happening, and many countries are already facing devastating consequences. Populations worldwide are adapting to the season\u27s unpredictability they relay to lands for agriculture. Our first research was to develop an IoT Clusters Platform for Data Collection, analysis, and visualization. The platform comprises hardware parts with Raspberry Pi and Arduino\u27s clusters connected to multiple sensors. The clusters transmit data collected in real-time to microservices-based servers where the data can be accessed and processed. Our objectives in developing this platform were to create an efficient data collection system, relatively cheap to implement and easy to deploy in any part of the world. Since we have completed the first part, we are implementing a study case for a field used of the platform. Thus, we are implementing an environment monitoring technology base on weather data. For this study, the platform will collect real-time environmental data using sensors (Temperature, humidity, light and ultraviolet sensors, and other sensors). We are setting those sensors in relatively limited superficies due to resources problem. Next, we will use this data to find patterns in weather changes using Machine and Deep learning techniques since these environmental data come from a designated area. The main objective of this part is to find a weather pattern using collected data specific to this area. Data collected during this research and the IoT platform are available on campus for students to use for their class projects or future research. Currently, we are in the data collection process. We also evaluate the degradation and environmental effects on devices and sensors used. This study case is a needed step in the IoT Clusters Platform for Data Collection, Analysis, and Visualization research project. At the end of the project, the data collection framework from it will be efficient and cost less

GR-182 - IoT Clusters Platform for Data Collection, Analysis, and Visualization Use Case

Climate change is happening, and many countries are already facing devastating consequences. Populations worldwide are adapting to the season\u27s unpredictability they relay to lands for agriculture. Our first research was to develop an IoT Clusters Platform for Data Collection, analysis, and visualization. The platform comprises hardware parts with Raspberry Pi and Arduino clusters connected to multiple sensors. The clusters transmit data collected in real-time to microservices-based servers where the data can be accessed and processed. Our objectives in developing this platform were to create an efficient data collection system, relatively cheap to implement and easy to deploy in any part of the world. Since we have completed the first part, we are implementing a study case for a field used by the platform. Thus, we are implementing an environment monitoring technology base on weather data. For this study, the platform will collect real-time environmental data using sensors (Temperature, humidity, light and ultraviolet sensors, and other sensors). We are setting those sensors in relatively limited superficies due to resources problem. Next, we will use this data to find patterns in weather changes using Machine and Deep learning techniques since these environmental data come from a designated area. The main objective of this part is to find a weather pattern using collected data specific to this area. Data collected during this research and the IoT platform are available on campus for students to use for their class projects or future research. Currently, we are in the data collection process. We also evaluate the degradation and environmental effects on devices and sensors used. This study case is a needed step in the IoT Clusters Platform for Data Collection, Analysis, and Visualization research project. At the end of the project, the data collection framework will be efficient and cost less

Secure Cloud-based IoT Water Quality Gathering for Analysis and Visualization

Water quality refers to measurable water characteristics, including chemical, biological, physical, and radiological characteristics usually relative to human needs. Dumping waste and untreated sewage is the reason for water pollution and several diseases to the living hood. The quality of water can also have a significant impact on animals and plant ecosystems. Therefore, keeping track of water quality is a substantial national interest. Much research has been done for measuring water quality using sensors to prevent water pollution. In summary, those systems are built based on online and reagent-free water monitoring SCADA systems in wired networks. However, centralized servers, transmission protocols, and data access can present challenges and disadvantages for those systems. This paper proposes a secure Cloud-based IoT water quality gathering architecture for water quality analysis and visualization to address the limitations of the current systems. The proposed architecture will send, analyze and visualize water quality data in the Cloud by utilizing specialized sensors and IoT-based gateways to capture water measurements (Dioxygen concentration, and temperature, among others). Then, they communicate securely to the Cloud-based server through a high-speed wireless network. We evaluated the performance of the proposed framework on a process-oriented approach to success metrics for cyberinfrastructures. The experiments were conducted in a laboratory and focused on network security and resiliency, the IoT prototype performance in dropping real-time data transmission, and remote access. The results demonstrate higher data collection and transmission effectiveness with minimal data loss and low energy usage over time. The accompanying cloud-based platform provided the flexibility needed for water quality monitoring and laboratory studies

Niveau De Contamination Du Poivron (Capsicum L., 1753) Par Les Pesticides

The study was done on two species of peppers capsicumannuum and capsicum fructescens. It concerned ninety samples of these two species, collected during three countrysides in two localities of Côte d’Ivoire (Bouake and Dabou). These samples were handled by means of a liquid-phase leading chromatograph SHIMADZU with the aim of determining the residues of pesticides. The observed results revealed a contamination of both species : capsicum annuum and capsicum fructescens, indeed, six residues of pesticides (chlorothalonil, chlorpyrifos, carbendazim, maneb, dimethoate and lambdacyaholothrine) were detected in these two species distributed in four families of pesticides (organochlorines, organophosphates, carbamates and pyrethrinoïds). The analysis showed that pyrethrinoïdes with respective proportions of 76,17% and 75,95% in capsicum annuum and capsicum fructescens were the most important ; followed organophosphate with respective proportions of 10,93% and 20,04% in capsicum annuum and capsicum fructescens.The study also showed that the concentrations of residues of pesticides detected in the edible part (pericarp ) peppers are appreciably equal those found in the part inedible(pulp). However, the residues of pesticides detected in peppers of both localities have all average concentrations lower than the standards established by the Codex Alimentarius

Rift Valley Fever in Small Ruminants, Senegal, 2003

Serologic incidence was estimated at 2.9%