Elifadhili Daniel is our LandPKS Country Coordination Officer for Tanzania. He is a crop scientist, with a Master of Science Degree in Crop Science from Wageningen University and Bachelor of Science in Agriculture from Sokoine University of Agriculture. Daniel has more than 10 years’ experience working with farmers as an agricultural extensionist, three of which he worked as a researcher for AfricaRice where he was involved in developing cost effective, culturally and socially acceptable parasitic weed control strategies for resource-poor rice farmers in Tanzania. He has interacted and established a network with various agricultural stakeholders including input suppliers, researchers, Agricultural training institutes, local NGOs and District Agricultural Offices in Tanzania. His LandPKS work in Tanzania involves, among many things, training farmers, extension, development and researchers on the use of the LandPKS mobile app, identifying and communicating improvements to the LandPKS development team and developing additional training and outreach materials in Swahili.
Due to shortage of extension officers in many villages of Tanzania and high costs for conducting laboratory soil testing, Daniel is motivated ensure LandPKS is rolled out and used as a decision tool for soil management by multiple stakeholders and users.
The LandPKS Team would like to introduce Heather Brown, our new LandPKS Web Developer. Heather has been working hard to improve both the usability and usefulness of the LandPKS website over the past few months. Heather graduated with her Masters of Library and Information Science degree from San Jose State University in May 2016. Her focus was in web design and information architecture. Heather is responsible for designing and maintaining web pages of Land Potential and Portal websites. Her most recent project included constructing a new website for Land Potential with the help of several of our enigmatic team members.
In order to create the new site Heather had to research all available web builders to see which one would best serve our needs and enable the growth of our organization and project. Once the web builder was chosen she had to import all relevant data and text into the new site. With the help of our graphic designer and local coordinator, the theme, color scheme, and page images were chosen. With the new site up and running Heather will be responsible for the day-to-day maintenance of the site and providing assistance where needed. She is hoping to be able to develop plugins relevant to our project’s work and upload them to WordPress for more organizations to employ.
On a more personal note, Heather enjoys gardening, crafting, and trying new recipes. She believes that living in the southwest provides a fun challenge when trying to construct a garden.
Huong Tran is the Quality Assurance Coordinator for LandPKS. She is based in Las Cruces, NM and has been working with the project since Jan 2016. Huong’s primary roles with the project include creating test plans and test scenarios, working with software developers to ensure quality standards, and performing manual tests for various products of LandPKS. She enjoys catching LandPKS bugs before users do and is glad that she can contribute to provide confidence towards software quality.
Scenario testing is done to make sure that the end to end functioning of the LandPKS app and all the process flows are working well. In scenario testing, the tester puts herself in the end user’s shoes and figures out the real world scenarios or use cases which can be performed on the app by the end user. Scenario testing helps testers to explore how the app will work in the hands of an end user. This is very important for catching bugs in the LandPKS app and designing the app with users’ needs in mind.
Even though the main goal of testing is to be able to detect and catch many of the bugs, the automated tools cannot test for visual considerations like gestures, image color or font size. However, the manual testing that Huong does can judge these types of app features. Manual testing can also test the User Experience and User Interface. Any bugs in data connection and/or slope measurement, which are two critical functionalities of the LandPKS app, can also be caught with manual testing
In light of the fact that access to an Internet connection in Africa is still limited, Huong has prioritized her testing efforts and focused on the reliability of the apps in an unstable data connection environment. She has tried to replicate the scenarios that a common end user might face when s/he is in the field collecting data and using the app. Her tests are done to ensure that the GPS is still working well, the app is behaving as expected, and that entered data is saved when there is no network or data connection.
Thanh Nguyen is a PhD candidate in the Computer Science Department at New Mexico State University. Thanh has been working on the LandPKS project for several years now and has taken a critical role in the development of the LandPKS app. During his time with LandPKS, he has worked on the following:
Developed Data Analytics System and Prediction Model that applied Machine Learning Algorithms to get as much knowledge as possible from the soil profile, weather, and water data to build models for analyzing soil potential.
Developed the LandPKS Database and LandPKS API System that allowed developers and users to interact with and access LandPKS data (LandInfo, LandCover, etc). LandPKS Database and API System are hosted in Google Cloud Platform and people can visit: https://api.landpotential.org
Developed Web Data Portal to allow users to have the ability to access and download LandPKS data in Web Browser. In addition, the Data Portal provides tools that analyze and displays the user data.
Developed LandPKS mobile application that allows users to collect and interact with LandPKS data in Android and iOS.
Developed Big-Data processing module using Map-Reduce (Hadoop) to create accessible climate data and soil profiles for all locations in the world
Thanh graduated with his Masters of Computer Science at James Cook University in Australia. His thesis, entitled Data Mining in Internet Banking, is currently being used in a number of Asian banks. His research interests include Data Mining and Knowledge Discovery (classification, clustering, association rules and prediction models), Artificial Intelligence (knowledge representation and reasoning, planning, logic programming, answer set programming and Web semantics – Services Composition), Machine Learning and Collective Intelligence (recommendation system, discovering groups, searching and ranking, collaborative filtering, document filtering, generative modelling, advanced classification, etc.) and Big-Data processing. His primary research now focuses on Automation Web Services Composition in Web Semantics. He is developing a completed end-to-end AI system to collect requirements from users in Natural Language and explore workflows that can satisfy the users requirements automatically. After the workflow is achieved, our system is able to execute each Web Service component in workflow sequence in order to achieve the goal.
Brent, an undergraduate student at New Mexico State University, has been working with LandPKS on the API (Application Programming Interface) and an automated build and testing suite. Whenever a change is made to any LandPKS app, the automation suite builds the newest version with the changes that were just made. After building these changes, the suite runs tests on the application that was changed to catch bugs or mistakes that may occur. The suite launch emulators for all the main operating systems and goes through input process. After inputting the data the suite then validates results from LandPKS models and creates tables and stores results in the tables. This system allows changes and bugs to be tested constantly and the results stored for tracking purposes.
The LandPKS API on the backend is a single insertion and retrieval point. This allows anyone to send and receive data from a single point. This API integrates all the insertions and updates the plot areas whenever data is received. The API also integrates our models into the data as it received. The API allows all this multidirectional data flow to be unnoticeable and easily manipulated to the end user. The API also allows anyone to use our data in other applications with simple http requests. When a request for a site is received, the API retrieves all the relevant data and returns the results via the same query. Integrated into the LandPKS API is “API Explorer” which allows anyone to become acquainted with the “API” by showing the types of requests that can be passed as well as the responses received.
Brent Barnett is a dual undergrad student in the Chemical Engineering Department and the Computer Science Department at New Mexico State University. He is a transfer student from Austin, Texas. He has worked with automation and database engineering for six years. Prior to joining Jornada he worked for Versasuite and IBM as a software and database engineer respectively. His primary roles are build/test automation and LPKS API development. His interests include database development, prediction algorithms, process design and automation.