Communication protocols evaluation for a wireless rainfall monitoring network in an urban area

Rainfall monitoring networks are key elements for the development of alerts and prediction models for communities at risk of flooding during high intensity rainfall events. Currently, most of these networks send the precipitation measurement to a data center in real-time using wireless communication protocols, avoiding travel to the measurement site. An Early Warning System (EWS) for pluvial flash floods developed in Barranquilla (Colombia), used the GPRS protocol to send rain gauge data in real-time to a web server for further processing; however, this protocol has a high consumption of energy and also high maintenance costs. This article carried out an evaluation in terms of link budget, link profile, energy consumption and devices costs of three low-power wireless communication protocols, Zigbee, LoRaWAN and Sigfox, to determine which one is the most suitable for the EWS of the city of Barranquilla. To perform the evaluation, a wireless sensor network was designed and characterized for Zigbee and LoRaWAN with Radio Mobile tool taking into account the measurement points implemented with GPRS network. The evaluation included the power consumption of Zigbee, LoRaWAN and Sigfox. From the results of simulations, LoRaWAN and Zigbee network has similar radio signal received and the LoRaWAN network obtains the least losses per path. As for power consumption, the LoRaWAN devices has the lowest energy consumption, as well as, the LoRaWAN network sensor nodes are cheaper. Finally, the protocol with the best general performance was LoRAWAN, since complies with the communication, consumption and cost requirements

Efficient approaches to agile cost estimation in software industries: a project-based case study

Agile was invented to improve and overcome the traditional deficiencies of software development. At present, the agile model is used in software development very vastly due to its support to developers and clients. Agile methodology increases the interaction between the developer-client, and it makes software product defects free. The agile model is fast and becoming more popular because of its features and flexibility. The study shows that the agile software development model is an efficient and effective software development strategy that easily accommodates user changes, but it is not free from errors or shortcomings. The study shows that COCOMO and Planning Poker are famous cost estimation procedures, but are not ingenious for agile development. We conduct a study on real-time projects from multinational software industries using different estimation approaches to estimate the project’s cost and time. We thoroughly explain these projects with the limitations of the techniques. The study has proven that the traditional and modern estimation approaches still have limitations to accurate estimation of projects

A Cost Estimating Method for Agile Software Development

In every software development project, the software effort estimating procedure is an important process in software engineering and always critical. The consistency of effort and timeline estimation, along with several factors, determines whether a project succeeds or fails. Both academics and professionals worked on the estimation approaches in software engineering. But, all these approaches have many problems that need to be addressed. One of the most difficult aspects of software engineering is estimating effort in agile development. This study aims to provide an effort estimation method for agile software development projects. Because in software engineering, the agile method is widely used for the development of software applications. The development and usage of the agile method are described in depth in this study. The framework is configured with empirical data gathered by projects from the software industry. The test findings reveal that the estimation method has great estimation accuracy in respect of mean magnitude of relative error (MMRE) and Prediction of Error PRED (n). The suggested approach achieves more accuracy for effort estimation as compare to others

Gas sensing system using an unmanned aerial vehicle

A prototype is designed for the analysis of CO2 concentration. In this paper, to evaluate its functionality, data sending tests are executed. A low cost E34-2G4H20D RF module installed in a UAV (unmanned aerial vehicle) is used for data transmission. CO2 concentration measurement were made at the “Universidad de la Costa” in Barranquilla - Colombia. For this, a device was built for monitor the concentration of CO2 using the Arduino UNO platform and the MQ135 gas sensor. Tests were carried out at different heights to analyze package loss and CO2 concentration levels. The results show the effectiveness of the RF module in all tests for data transmission. The concentration of CO2 is evaluated in three zones to determine the minimum and maximum levels in each of them

Predictive variables for agile development merging cloud computing services

Cloud Technology is a most challenging modern area in the field of modern technologies in whichassets(e.g.,CPUandcapacity)canberentedanddischargedbytheclientsthroughinterneton-demand basis. The cloud computing has been giving virtual computing services to a little, medium and extensive industries, and services, for example, infrastructure as a service (IaaS), platform as a service (PaaS), and softwareasaservice(SaaS).Cloudcomputinghasagreatcombinationwiththeagilesoftwaredevelopment as a research area. Many researchers worked in Agile Cloud field. The software industries are using the agile methodology for efficient software development need some platform to get quick feedback from the client. Therefore, the agile-cloud is a great combination for it but due to security reasons that directly influence the less adoption of cloud in software industries. This paper reports the survey results of software industries. The total of seven IT industries and many professionals was involved in this paper. However, this paper also contributes and reveals how existing issues can affect agile-cloud adoption for efficient software development. Furthermore, we do not find any type of survey conducted in Pakistan’s software industries-related to cloud-agile adoption

Combination of AHP and TOPSIS methods for the ranking of information security controls to overcome its obstructions under fuzzy environment

The organizations utilizing the cloud computing services are required to select suitable Information Security Controls (ISCs) to maintain data security and privacy. Many organizations bought popular products or traditional tools to select ISCs. However, selecting the wrong information security control without keeping in view severity of the risk, budgetary constraints, measures cost, and implementation and mitigation time may lead to leakage of data and resultantly, organizations may lose their user’s information, face financial implications, even reputation of the organization may be damaged. Therefore, the organizations should evaluate each control based on certain criteria like implementation time, mitigation time, exploitation time, risk, budgetary constraints, and previous effectiveness of the control under review. In this article, the authors utilized the methodologies of the Multi Criteria Decision Making (MCDM), Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to help the cloud organizations in the prioritization and selection of the best information security control. Furthermore, a numerical example is also given, depicting the step by step utilization of the method in cloud organizations for the prioritization of the information security controls

Artificial intelligence-based Kubernetes container for scheduling nodes of energy composition

Kubernetes is a portable, extensible, open-source platform for managing containerized workloads and services that facilitates both declarative configuration and automation. This study presents Kubernetes Container Scheduling Strategy (KCSS) based on Artificial Intelligence (AI) that can assist in decision making to control the scheduling and shifting of load to nodes. The aim is to improve the container’s schedule requested digitally from users to enhance the efficiency in scheduling and reduce cost. The constraints associated with the existing container scheduling techniques which often assign a node to every new container based on a personal criterion by relying on individual terms has been greatly improved by the new system presented in this study. The KCSS presented in this study provides multicriteria node selection based on artificial intelligence in terms of decision making systems thereby giving the scheduler a broad picture of the cloud's condition and the user's requirements. AI Scheduler allows users to easily make use of fractional Graphics Processing Units (GPUs), integer GPUs, and multiple-nodes of GPUs, for distributed training on Kubernetes. © 2021, The Society for Reliability Engineering, Quality and Operations Management (SREQOM), India and The Division of Operation and Maintenance, Lulea University of Technology, Sweden

Real time monitoring system for the detection of saline wedge in the Magdalena River – Colombia

This article aims to socialize the results of the development and implementation of a system based on IOT for aquifers, with its application in the estuary of the Rio Magdalena in Colombia. The SISME software supports the identification processes of different factors that can influence the appearance of the saline wedge in the navigable channel of the river. These aspects bring about the improvement of maritime safety and, in turn, allow us to know different aspects related to behavior through continuous sensing of the river. This article shows both the characterization of this river as well as studies related to it and the location of the sensors and description of the software developed