was designed targeting a robust low-power low-cost AWS that would be replicated so as to increase the density of AWSs in East Africa under the WIMEA-ICT project (www.wimea-ict.net). It was the first IoT designed in the IoT-ra lab and its accuracy is comparable to market-grade AWS. Our AWS is much more affordable (costs approximately USD 1,000), is solar-powered, and generally robust. The WIMEA-ICT AWS is composed of different meteorological sensors structured under three nodes, a gateway and a remote server. The nodes are named according to the position and/or the heights of the sensors above the ground. The nodes that make up the WIMEA-ICT AWS are; the 2m node that has sensors for reading the relative humidity and the atmospheric temperature values, the 10m node has sensors that read the wind speed, the wind direction and the solar insolation values. The ground node contains sensors that read the soil temperature, soil moisture, pressure and the rainfall/or precipitation values. The gateway is a combination of the sink node that receives the weather data reports broadcasted by the three (10m, 2m and ground) nodes and the particle electron with the GSM module for the internet connection to the server. At the gateway, the RTC module attaches the timestamp to the report received by the sink and the SD card temporarily stores the sensor data report before it is uploaded to the server. After a successful benchmarking of the sensors against WMO acceptable sensors, 70 AWSs were deployed in the East Africa region i.e. 30 AWSs in Uganda, 30 AWSs in Tanzania and 10 AWSs in South Sudan.

WIDS provides two platforms including: i) a mobile-based USSD; and ii) web applications for Meteorological agencies to capture weather products such as forecasts and weather advisories and to disseminate the information to the public. It was a designed under the WIMEA-ICT project (https://wids.unma.go.ug). The information provided by the system includes weather forecasts across all districts/states in the country and advisory information on agriculture and food security, disaster preparedness, heath and water. WIDS provides the following features: Interface for accessing advisories and weather forecasts especially for the farmers. Weather forecasts include daily forecasts, decadal (10-day forecasts) and seasonal forecasts Interface for capturing feedback on the advisories and forecasts from farmers. Interface for administrators to enter advisories and weather forecasts.Interface for farmers and other stakeholders to view advisories and weather forecasts. Interface for administrators to view farmer/ stakeholder feedback .Interface for administrators to add users to the system. Interface for administrators to view statistical information on user requests and other parameters

An open source, web-based, desktop-based and mobile-based weather data management software, developed under the WIMEA-ICT project (www.wimea-ict.net). The WDR was developed having conducted a bench-marking exercise and analysed the realities in a developing country-context and the need for appropriate technology solutions. It was developed for storage of weather observations entered at manual weather stations as well as received from automatic weather stations (AWS) in real time via an API that forwards the data from the AWS sync. Due to the intermittence of electric power supply, unreliable internet connectivity and low usability of computers and smartphones in remote areas, the WDR was built to also accept data entered using a basic feature-phone via sms. WDR has the following features:The data is stored in the most basic and raw format at an hourly interval in order to enable modeling, scalability and flexibility in data processing and retrieval.In real-time, the WDR enables retrieval of customized and traditional meteorological reports, which include Meteorological Aerodrome Reports (METAR), Synoptic reports, Weather summary reports, Dekadal reports, Rainfall reports, Sunshine reports, etc. in order to meet the needs of both a meteorological data agency and users from different sectors of application.The WDR also provides for data rescue so that image/scanned files of historical weather records, which were previously recorded in print, can be uploaded and the data entered/digitized.Only authenticated users are allowed to retrieve historical data reports or download rescued data files.The WDR is built to be managed by meteorological data workflow managers and has accounts for different users within a meteorological data workflow. Authentication is required for different access levels. Functionalities have also been differentiated according to the roles within a typical meteorological workflow to enforce data security, data integrity and quality control mechanisms.Given that the WDR is an open source software solution, it is customisable according to user needs.

The IMAgINe research project funded by GCRF (UK) was premised on the fact that the value of weather information in solving challenges of the various sectors is unappreciated. The result of this is a lukewarm investment in the weather services as well as hampered utilisation of the few available products inspite of several weather-related problems being experienced in the African continent. A multi-sectorial approach used to bring different stakeholders on the table to drive the use of weather information (forecasts and corresponding advisories) through the optimal use of ICTs.A mobile and web-based Weather Information Dissemination System (WIDS) tool was customised for each country and deployed to grant weather information access to the different sector representatives in the target countries. Then we undertook a study to assess the efficiency of this ICT tool. The results showed that there is a need for timely weather information to plan farming activities such as planting and application of fertilizers and pesticides as well as to manage flood and drought by the water sector and disaster management. Results further showed that the majority of the respondents have access to the technology and needed to access weather and climate information. The respondents who received weather information noted that the forecast was useful, however pointed to a need for improved collaborations between the meteorological authorities, ICT service providers, policymakers and farmers to facilitate an effective approach to weather information access and dissemination. Case Studies were conducted in Uganda, South Sudan and Nigeria.

The Project, “Tailoring Climate Services For Improved Agricultural Production”, i.e. LOCATE was supported by the Government of Uganda through the Research and Innovation Fund of Makerere University. It was designed to tailor climatic services to agriculture and thereby improve agricultural planning and production.The project:Contributed towards developing local capacities in weather prediction products and related services;Enhanced the production and usefulness of climatic services like the seasonal weather prediction forecasts;Developed procedures and tools to weather predictions to agriculture by customizing the World Food Studies Model. i.e. the WoFOST Model;Enhanced weather information dissemination systems.

It is a collaborative initiative where The Norwegian University of Science and Technology (NTNU), in partnership with Makerere University (Mak), University of Juba (UoJ), Dar-es-salaam Institute of Technology (DIT) and University of Bergen (UoB) received as a grant from NORAD, the Norwegian Agency for Development Cooperation under its NORHED II programme.
The AdEMNEA project, through various work packages is working with various diverse researchers and students to design, develop, and deploy a flexible network of data gathering and monitoring stations for meteorological data as well as a wide variety of data including audio, image, and video data as well as field reports and telemetry data, integrating both existing sensing platforms and customised components for specific research areas targeting Climate Change and Natural Resources.
These data points will be aggregated through resilient and energy-efficient ICT networks from the field to researchers conducting data analysis using machine learning, pattern recognition, and other artificial intelligence and analytical methods in order to support researchers in the application domain. The targeted application domains will be weather monitoring, building on the results and infrastructure established in the NORHED WIMEA-ICT project, and using this data together with the additional sensing and measurement sources to support researchers initially in the entomology domain.
The Work packages involved include:
(i) WP1 - Networks and Resilience
(ii) WP2 - Sensors and Signal Processing
(iii) WP3 - Data Analytics for Environment Monitoring Services