ECAWsoft: A Web based Climate and Weather Data Visualization for Big Data Analysis

Purpose: In Tanzania, data for climate and weather are normally analyzed by Meteorological Agency and then are published through TV, website and radio. Different stakeholders normally obtain the weather and climate data / information in a generalized way. This calls for a need of a system which allows data to be shared openly to different stakeholders so that they can analyze those data as per their specific needs. The paper presents the overview of the developed system, ECAWsoft. Also, it gives some few interfaces showing different outputs from the system. Findings: The goal of this paper has been attained by developing a working data visualization tool for climate and weather called ECAWsoft. The system is current operational and is providing open data for different stakeholders. It is user friendly and interactive with capability of displaying visualization of data as per fine granularity required by user. Development of open data system for data visualization has lead to a transparency system which is helping farmers, researchers, policy makers (etc.) to make informed decision on weather and climate. Practical implications: The system presented in this paper need to be scaled up so that more data from all weather stations in Tanzania can be populated in real time. Originality/value: The development and adoption of open systems for visualizing weather and climate data remains seriously lacking in many countries including Tanzania. This paper provides an overview of some initiative to fill such a research gap

Failure to return pillbox is a predictor of being lost to follow-up among people living with HIV on antiretroviral therapy in rural Tanzania

OBJECTIVES: Pill count is used to assess drug adherence in people living with HIV (PLHIV). Carrying a pillbox is associated with fear of concealment and stigma and might indicate poor adherence and predict someone who will be lost to follow-up (LTFU). We therefore assessed the association between pillbox return and being LTFU in rural Tanzania. METHODS: This is a nested study of the Kilombero and Ulanga Antiretroviral Cohort (KIULARCO). We included PLHIV aged >/= 18 years enrolled in KIULARCO between January 2013 and March 2019 with follow-up through January 2020, who were on antiretroviral treatment (ART) for >/= 6 months. Baseline was defined as the latest ART initiation or KIULARCO enrolment. We determined the association between time-dependent failed pillbox return updated at every visit and LTFU using Kaplan-Meier estimation and Cox models. RESULTS: Among 2552 PLHIV included in the study, 1735 (68.0%) were female, 959 (40.3%) had a WHO stage III/IV and 1487 (66.4%) had a CD4 cell count < 350 cells/microL. The median age was 38.4 years [interquartile range (IQR): 31.7-46.2]. During a median follow-up of 33.1 months (IQR: 17.5-52.4), 909 (35.6%) participants were LTFU, 43 (1.7%) died and 194 (7.6%) had transferred to another clinic. The probability of being LTFU was higher among PLHIV with failed pillbox return than among those who returned their pillbox [30.0%, 95% confidence interval (CI): 26.8-33.2% vs. 19.4%, 95% CI: 17.4-21.6%, respectively, at 24 months (hazard ratio = 1.67, 95% CI: 1.46-1.90; p < 0.001)]. CONCLUSIONS: Failed pillbox return was associated with a higher risk of being LTFU and could be used as a simple tool to identify PLHIV for appropriate interventions to reduce their chance of being LTFU

Experts’ assignment algorithm for Cloud-based Agro-advisory Service Information System (CASIS) using weighted sum model: piloting CASIS

A Cloud-based Agro-advisory Service Information System (CASIS) uses interactive operating mode where assignment of questions from farmers to experts is done manually. Questions as input to the system are received randomly in a day and experts are supposed to respond within a specified time. The system has 20 experts in its database who respond to farmers questions and it can receive more than 30 questions per day. If there is a significant delay in the responses to a question then the question is reassigned to another expert. Each expert behaves differently when responding to their assigned questions. In order to address the shortcomings, the experts’ assignment algorithm was developed utilizing the respondents’ response probabilities and time of responses. Assignment decision is based on using a model that trains ‘CASIS’ on the determination of best experts. CASIS training algorithm is developed to complement current weakness. The algorithm doesn’t omit experts who respond late but complements them with active ones. The decision boundary is homogeneity and numerical so as to give a single output quickly. The input (x1, x2) and output (y) variables are numeric. The main concept is that the output is generated using linear combination or weighted sum model The algorithm considers response time as best criteria to satisfy the farmers who send the questions. This algorithm provides a great chance of finding a quick answer within a short period of time. Automatic expert assignment is essential to achieve high adoption of the system that satisfies the on-time farmer advisories demand and promote efficiency as well as effective extension services for rural development

The use of participatory approaches in developing ICT-based systems for disseminating agricultural knowledge and information for farmers in developing countries: the case of Tanzania

The Electronic Journal of Information Systems in Developing Countries- EJISDC (2017) 78, 8, 1-23This paper provides an insight on the use of various participatory approaches to develop ICTs to the rural farming communities. The paper shows how collective groups of farmers can be empowered through involvement of different stakeholders in a participatory action research. The paper also discusses how participatory action research will help the farming community in adopting ICT-based solutions for agriculture. This in turn will contribute in solving problems as well as assisting decision making in identifying technological and agricultural needs. In this study, a total of 64 researchers and extension workers and 320 rural farmers were involved. Primary data were collected using a self-administered questionnaire and interviews. Data were analyzed using descriptive statistics tool. The results indicate that many ICT- based solutions for agriculture are not adopted by farmers and other stakeholders in various agricultural value chains because those ICTs were developed without using participatory approaches. Moreover, the results from study indicate that participatory action research approaches such as Participatory Communication (PV), Participatory Video (PV), Participatory Learning and Action Research (PLAR), Farmer Participatory Research (FPR), Informal-Mobile Learning Research (IMLR) have a significant impact on the effective use of ICTs in rural farming community and the agricultural domain in general. Among of these participatory approaches, the IMLR and PLAR have shown to be more effective because of availability and interactive mobile learning environments that excite interests, commitments and encourages participatory attitudes among famers and researchers. This study provides an evident that ICTs has a dominant position to alleviate rural poverty and strengthen the agriculture productivity through participatory approaches. We recommend that a strong commitment of all actors in agriculture value chain is needed so that they can collaborate to identify the problem, analysis and design possible solutions and finally, implement and later on use those developed ICTs to increase agriculture productivity

The use of participatory approaches in developing ICT-based systems for disseminating agricultural knowledge and information for farmers in developing countries: the case of Tanzania

The Electronic Journal of Information Systems in Developing Countries- EJISDC (2017) 78, 8, 1-23This paper provides an insight on the use of various participatory approaches to develop ICTs to the rural farming communities. The paper shows how collective groups of farmers can be empowered through involvement of different stakeholders in a participatory action research. The paper also discusses how participatory action research will help the farming community in adopting ICT-based solutions for agriculture. This in turn will contribute in solving problems as well as assisting decision making in identifying technological and agricultural needs. In this study, a total of 64 researchers and extension workers and 320 rural farmers were involved. Primary data were collected using a self-administered questionnaire and interviews. Data were analyzed using descriptive statistics tool. The results indicate that many ICT- based solutions for agriculture are not adopted by farmers and other stakeholders in various agricultural value chains because those ICTs were developed without using participatory approaches. Moreover, the results from study indicate that participatory action research approaches such as Participatory Communication (PV), Participatory Video (PV), Participatory Learning and Action Research (PLAR), Farmer Participatory Research (FPR), Informal-Mobile Learning Research (IMLR) have a significant impact on the effective use of ICTs in rural farming community and the agricultural domain in general. Among of these participatory approaches, the IMLR and PLAR have shown to be more effective because of availability and interactive mobile learning environments that excite interests, commitments and encourages participatory attitudes among famers and researchers. This study provides an evident that ICTs has a dominant position to alleviate rural poverty and strengthen the agriculture productivity through participatory approaches. We recommend that a strong commitment of all actors in agriculture value chain is needed so that they can collaborate to identify the problem, analysis and design possible solutions and finally, implement and later on use those developed ICTs to increase agriculture productivity

Meta-Analysis Assessing Potential of Drone Remote Sensing in Estimating Plant Traits Related to Nitrogen Use Efficiency

Unmanned Aerial Systems (UASs) are increasingly vital in precision agriculture, offering detailed, real-time insights into plant health across multiple spectral domains. However, this technology’s precision in estimating plant traits associated with Nitrogen Use Efficiency (NUE), and the factors affecting this precision, are not well-documented. This review examines the capabilities of UASs in assessing NUE in crops. Our analysis specifically highlights how different growth stages critically influence NUE and biomass assessments in crops and reveals a significant impact of specific signal processing techniques and sensor types on the accuracy of remote sensing data. Optimized flight parameters and precise sensor calibration are underscored as key for ensuring the reliability and validity of collected data. Additionally, the review delves into how different canopy structures, like planophile and erect leaf orientations, uniquely influence spectral data interpretation. The study also recognizes the untapped potential of image texture features in UAV-based remote sensing for detailed analysis of canopy micro-architecture. Overall, this research not only underscores the transformative impact of UAS technology on agricultural productivity and sustainability but also demonstrates its potential in providing more accurate and comprehensive insights for effective crop health and nutrient management strategies

ECAWsoft: A web based climate and weather data visualization for big data analysis

In Tanzania, data for climate and weather are normally analyzed by Meteorological Agency and then are published through TV, website and radio. Different stakeholders normally obtain the weather and climate data / information in a generalized way. This calls for a need of a system which allows data to be shared openly to different stakeholders so that they can analyze those data as per their specific needs. Design/methodology/approach: The paper presents the overview of the developed system, ECAWsoft. Also, it gives some few interfaces showing different outputs from the system. Findings: The goal of this paper has been attained by developing a working data visualization tool for climate and weather called ECAWsoft. The system is current operational and is providing open data for different stakeholders

A Review of Successes and Impeding Challenges of IoT-Based Insect Pest Detection Systems for Estimating Agroecosystem Health and Productivity of Cotton

Using artificial intelligence (AI) and the IoT (Internet of Things) is a primary focus of applied engineering research to improve agricultural efficiency. This review paper summarizes the engagement of artificial intelligence models and IoT techniques in detecting, classifying, and counting cotton insect pests and corresponding beneficial insects. The effectiveness and limitations of AI and IoT techniques in various cotton agricultural settings were comprehensively reviewed. This review indicates that insects can be detected with an accuracy of between 70 and 98% using camera/microphone sensors and enhanced deep learning algorithms. However, despite the numerous pests and beneficial insects, only a few species were targeted for detection and classification by AI and IoT systems. Not surprisingly, due to the challenges of identifying immature and predatory insects, few studies have designed systems to detect and characterize them. The location of the insects, sufficient data size, concentrated insects on the image, and similarity in species appearance are major obstacles when implementing AI. Similarly, IoT is constrained by a lack of effective field distance between sensors when targeting insects according to their estimated population size. Based on this study, the number of pest species monitored by AI and IoT technologies should be increased while improving the system’s detection accuracy

Experimenting open agricultural extension service in Tanzania: A case of Kilosa Open Data Initiative (KODI)

Journal of Scientific and Engineering Research, 2016, 3(6):116-124This paper presents results from the application of Open Data System to improve coverage of agricultural extension services using web-based and mobile-based farmers‘ advisory information Ushaurikilimo in Kilosa District. The research adopted a participatory action research method to develop the interventions. The findings from this study show that farmers and other actors get timely, relevant and personalized advisory services. The user interface of the Open System hosting Open Data is in Swahili language, a language widely spoken in the study area, which enhanced adoption of the system. The Open System did not require farmers and other actors to pay for the services, which motivated to attract farmers and actors to adopt the system. In order to lower the cost of implementing the project, agricultural extension officers in study villages were used to receive questions from farmers and provided answers, and sent difficulty questions to experts from Sokoine University of Agriculture to answer via their mobile phones