Master

src/assets/csv/technology_radar_dataset_updated_v9.csv

@@ -6,7 +6,6 @@ Unnamed: 0,Ideas/Concepts/Examples,Description,Theme,Use Case,Status/Maturity,Di
 4,Understanding Population Movement After the 2018 Central Sulawesi Natural Disasters,"After the massive earthquake struck Central Sulawesi, Indonesia in September 2018, through a shared value partnership with mobile telecom Digicel, Pulse Lab Jakarta (PLJ) over the past few years has investigated how pseudonymised mobile network data from subscribers in the Pacific region can be used to support evidence-based decision making. From modelling population displacement to understanding changes in citizens behaviour after natural disasters, the research has yielded actionable insights for policymakers and a wealth of experiential knowledge.",Disaster Risk Management ,Disaster Relief logistic/resource allocation ,prototype,response,"Data Collection, Data Analysis, Cyber Physical Systems, Geographical Information Systems",Earthquakes,Asia,South-eastern Asia,Indonesia," Digicel, International Organisation for Migration (IOM)",UN Pulse Lab Jakarta,"Mobile Network Data, Spatial Data",SDG 9,2019,https://www.unglobalpulse.org/2019/12/understanding-population-movement-after-the-2018-central-sulawesi-natural-disasters/,https://www.unglobalpulse.org/wp-content/uploads/2019/12/PLJ-Palu-visualization.webp
 5,Understanding Population Movement After the 2018 Central Sulawesi Natural Disasters,"After the massive earthquake struck Central Sulawesi, Indonesia in September 2018, through a shared value partnership with mobile telecom Digicel, Pulse Lab Jakarta (PLJ) over the past few years has investigated how pseudonymised mobile network data from subscribers in the Pacific region can be used to support evidence-based decision making. From modelling population displacement to understanding changes in citizens behaviour after natural disasters, the research has yielded actionable insights for policymakers and a wealth of experiential knowledge.",Disaster Risk Management ,Disaster Relief logistic/resource allocation ,prototype,mitigation,"Data Collection, Data Analysis, Cyber Physical Systems, Geographical Information Systems",Earthquakes,Asia,South-eastern Asia,Indonesia," Digicel, International Organisation for Migration (IOM)",UN Pulse Lab Jakarta,"Mobile Network Data, Spatial Data",SDG 9,2019,https://www.unglobalpulse.org/2019/12/understanding-population-movement-after-the-2018-central-sulawesi-natural-disasters/,https://www.unglobalpulse.org/wp-content/uploads/2019/12/PLJ-Palu-visualization.webp
 6,Quantifying Real-Time Rainfall Intensity in Bosnia and Herzegovina,"Accurate, spatially dense real-time rainfall measurements are essential for water management of any region, which in turn impacts agriculture, transportation and mobility, energy and weather hazards. After the war in Bosnia and Herzegovina, only 100 out of 500 rainfall stations have remained operational, hampering its spatial hydrological data collection. The project employs Big Data and Machine Learning, to fill in the missing gap by turning CCTV footage and videos obtained by smartphones into a real-time rainfall observation, allowing for accurately geo-referenced and cost-effective data collection. All the information collected is then available on the web portal and enable the authorities to be better prepared for meteorologically and hydrologically based hazards and associated risks for the population and to lead to a better-informed policymaking.","Environment, Agriculture",Situational awareness/actionable information gathering,prototype,recovery,"Data Collection, Big Data, Artificial Intelligence, Machine Learning, Computer Vision, Natural Language Processing, Cloud Computing",Climate Change,Europe,Southern Europe,Bosnia and Herzegovina ,"Aqua Procon s.r.o., H2I Balkans D.O.O. Sarajevo","UNDP, UNDP Bosnia and Herzegovina",Spatial Data,SDG 13,2020,https://undp.cz/portfolio-item/quantifying-real-time-rainfall-intensity-in-bosnia-and-herzegovina/,https://undp.cz/wp-content/uploads/2020/04/7.jpg
-7,"Measuring, Mapping and Forecasting  Air Pollution","With increasing traffic and  worsening global air pollution Belarus is facing the challenge of worsening air quality. Belarus UNDP partnered with Polish tech start-up Airly to implement an innovative solution that will allow constant monitoring of the situation in order to help prepare for possible threats and even take actions to prevent them. Airly sensors collect the data on air quality, and by using machine learning technology, Airly also provides reliable forecasts, which as a whole is a very powerful tool in the fight against air pollution and its effects.","Environment, Pollution",Situational awareness/actionable information gathering,production,mitigation ,"Data Collection, Data Analysis, Artificial Intelligence, Machine Learning, Cyber Physical Systems",Air Pollution,Europe,Eastern Europe,Belarus,"Airly, VidaLink, Ministry of Foreign Affairs of the Republic of Poland.","UNDP, UNDP Polish Challenge Fund, UNDP Belarus",Sensor Data,"SDG 3, SDG 13, SDG 15",2021,https://airly.eu/en/blog/exchange-of-air-pollution-monitoring-and-forecasting-solutions-using-machine-learning-technologies-and-analytics/,https://airly.org/en/static/d5888dee5c13eec10f5ec81e1b5bc234/6dbf1/UNDP-image-1.jpg
 8,Computer Vision Flood Forecasting using Remotely Sensed Data,"Regional flood forecasting and modeling is a big problem in the hydrological sciences. The issue is even more pronounced in Bosnia and Herzegovina due to inadequate hydro meteorological monitoring network, where only 100 out of 500 rainfall stations remained operational after the war. The project solicits the latest technology from different fields: Remote Sensing to acquire Earth Observations (EO) data, Computer Vision to process these data and Machine Learning (ML) to develop models in order to relate meteorological and other EO data with flooding. The approach is deployed to address one of the most pressing problems B&H currently faces increasingly frequent occurrence of floods, and shall result in accurate models of rainfal runoff behavior's, which would help Water Agencies and the Federal Hydro Meteorological Institute with flood prediction and management.",Sustainable management of natural resources,Disaster assessment/prediction and early warning systems,production,preparedness,"Data Collection, Artificial Intelligence, Machine Learning, Computer Vision, Remote Sensing, Mobile App",Floods,Europe,"Eastern Europe, Southern Europe","Bosnia and Herzegovina,  Czechia"," GISAT, H2I Balkans ","UNDP, UNDP Bosnia and Herzegovina",Spatial Data,SDG 13,2020,https://undp.cz/portfolio-item/computer-vision-flood-forecasting-using-remotely-sensed-data/,https://undp.cz/wp-content/uploads/2020/09/gisat.jpg
 9,C Bot ChatBot ,"AI-based chatboat assists Georgian businesses and the more than 125,000 residents of Rustavi by keeping them informed about city services, new regulations, and steps to take to cope with coronavirus challenges without leaving their homes.",Pandemic/Epidemic,Emergency communications,production,preparedness,"Chatbot, Artificial Intelligence, Natural Language Processing",Pandemic/Epidemic,Asia,Western Asia,Georgia,"Rustavi Innovations Hub, Rustavi Municipality, EU4Business","UNDP, UNDP Georgia",Text Data,SDG 3,2020,https://eu4georgia.ge/c-bot-chatbot-with-ai-keeps-georgian-business-informed-during-pandemic/,https://eu4georgia.eu/wp-content/themes/yootheme/cache/Banner_-01-729de3fc.jpeg
 10,C Bot ChatBot ,"AI-based chatboat assists Georgian businesses and the more than 125,000 residents of Rustavi by keeping them informed about city services, new regulations, and steps to take to cope with coronavirus challenges without leaving their homes.",Pandemic/Epidemic,Emergency communications,production,recovery,"Chatbot, Artificial Intelligence, Natural Language Processing",Pandemic/Epidemic,Asia,Western Asia,Georgia,"Rustavi Innovations Hub, Rustavi Municipality, EU4Business","UNDP, UNDP Georgia",Text Data,SDG 3,2020,https://eu4georgia.ge/c-bot-chatbot-with-ai-keeps-georgian-business-informed-during-pandemic/,https://eu4georgia.eu/wp-content/themes/yootheme/cache/Banner_-01-729de3fc.jpeg

src/helpers/ProjectFormFields.tsx

@@ -58,7 +58,7 @@ export const ProjectFormFields: React.FC<Props> = ({
           name={label}
           value={projectFormValues[label as keyof ProjectFieldValues]}
           onChange={handleChange}
-          data-testId={`field-${label}`}
+          data-testId={`field-${String(label)}`}
         />
       );
     case 'textArea':
@@ -69,7 +69,7 @@ export const ProjectFormFields: React.FC<Props> = ({
           name={label}
           value={projectFormValues[label as keyof ProjectFieldValues]}
           size='sm'
-          data-testId={`field-${label}`}
+          data-testId={`field-${String(label)}`}
         />
       );
 
@@ -81,7 +81,7 @@ export const ProjectFormFields: React.FC<Props> = ({
           name={label}
           value={projectFormValues[label as keyof ProjectFieldValues]}
           onChange={handleChange}
-          data-testId={`field-${label}`}
+          data-testId={`field-${String(label)}`}
         >
           {(options || []).map((option: any, idx: any) => (
             <option
@@ -100,7 +100,7 @@ export const ProjectFormFields: React.FC<Props> = ({
       return (
         <div
           style={{ width: '50%', maxWidth: '350px' }}
-          data-testId={`field-${label}`}
+          data-testId={`field-${String(label)}`}
         >
           <SelectMultiple
             options={options as Option[]}

src/navigation/AppNav.tsx

@@ -122,22 +122,25 @@ export const NavApp: React.FC = () => {
             <Route path={ROUTES.PROJECTS} element={<Outlet />}>
               <Route index element={<Projects />} />
               <Route
-                path={`${ROUTES.NEW}`}
+                path={String(ROUTES.NEW)}
                 element={<ProjectAction mode='add' />}
               />
-              <Route path={`${ROUTES.REVIEW}`} element={<ReviewProjects />} />
+              <Route
+                path={String(ROUTES.REVIEW)}
+                element={<ReviewProjects />}
+              />
 
               <Route path=':project_id' element={<ProjectDetails />} />
               <Route
-                path={`:project_id/${ROUTES.EDIT}`}
+                path={`:project_id/${String(ROUTES.EDIT)}`}
                 element={<ProjectAction mode='edit' />}
               />
             </Route>
 
             <Route path={ROUTES.DISASTERS} element={<Outlet />}>
               <Route index element={<Disasters />} />
               <Route
-                path={`${ROUTES.NEW}`}
+                path={String(ROUTES.NEW)}
                 element={
                   <InfoAction
                     mode='ADD'
@@ -147,7 +150,7 @@ export const NavApp: React.FC = () => {
                 }
               />
               <Route
-                path={`:id`}
+                path={':id'}
                 element={
                   <InfoDetails
                     tableName='disaster_types'
@@ -156,7 +159,7 @@ export const NavApp: React.FC = () => {
                 }
               />
               <Route
-                path={`:id/${ROUTES.EDIT}`}
+                path={`:id/${String(ROUTES.EDIT)}`}
                 element={
                   <InfoAction
                     mode='EDIT'
@@ -170,19 +173,19 @@ export const NavApp: React.FC = () => {
               <Route index element={<DisasterEvents />} />
               <Route path=':eventId' element={<DisasterEvent />} />
               <Route
-                path={`${ROUTES.NEW}`}
+                path={String(ROUTES.NEW)}
                 element={<EventAction mode='Add' />}
               />
               <Route
-                path={`:eventId/${ROUTES.EDIT}`}
+                path={`:eventId/${String(ROUTES.EDIT)}`}
                 element={<EventAction mode='Edit' />}
               />
             </Route>
 
             <Route path={ROUTES.TECHNOLOGIES} element={<Outlet />}>
               <Route index element={<Technologies />} />
               <Route
-                path={`${ROUTES.NEW}`}
+                path={String(ROUTES.NEW)}
                 element={
                   <InfoAction
                     mode='ADD'
@@ -192,7 +195,7 @@ export const NavApp: React.FC = () => {
                 }
               />
               <Route
-                path={`:id`}
+                path={':id'}
                 element={
                   <InfoDetails
                     tableName='technologies'
@@ -201,7 +204,7 @@ export const NavApp: React.FC = () => {
                 }
               />
               <Route
-                path={`:id/${ROUTES.EDIT}`}
+                path={`:id/${String(ROUTES.EDIT)}`}
                 element={
                   <InfoAction
                     mode='EDIT'

src/pages/projects/projectOverlay/projectOverlay.tsx

@@ -92,7 +92,7 @@ export const ProjectOverlay: React.FC<Props> = ({
   };
 
   const handleEdit = (): void => {
-    navigate(`/projects/${project.uuid}/edit`);
+    navigate(`/projects/${String(project.uuid)}/edit`);
     onClose();
   };
 
@@ -140,7 +140,7 @@ export const ProjectOverlay: React.FC<Props> = ({
                 src={imageUrl}
                 onLoad={handleImageLoad}
                 onError={handleImageError}
-                alt={`${project?.title || 'Project'} Image`}
+                alt={`${String(project?.title) || 'Project'} Image`}
                 style={{
                   width: '100%',
                   height: '100%',