Evidence from the ground.
Photos, locations and community reports give local teams a place to begin.
DHO COLLABORATION · A NATIONAL VISION
From reactive
to proactive
dengue defence.
AI-assisted larvae detection. Connected surveillance. A national vision for early prediction—bringing health authorities, hospitals, laboratories and communities together.
Developed with purpose.
In collaboration with DHO.
A CONNECTED VIEW OF PUBLIC HEALTH 01 / 07
STARTS IN THE FIELDA report. A location. A next step.
PD+7 roles, connected.One coordinated dengue response.
The real PHD dashboard. Screen values are demonstration data.
BUILT FOR PEOPLE.
CONNECTED BY PURPOSE.
CONNECTED BY PURPOSE.
07
Dedicated roles
13
Connected modules
01
Discover the idea Connected vision
01 / THE IDEA
A team effort deserves
a connected system.
A field observation matters. A lab result matters. An available hospital bed matters. Together, they can tell a much clearer story.
Dengue Guard AI brings these separate pieces into a shared workflow—from the person reporting a concern to the district coordinating action and the province overseeing the bigger picture.
Meet the purpose behind the platformContext at the district.
Field observations meet lab records, hospital capacity and operational resources.
A coordinated next step.
Relevant people receive alerts, assignments and the information they need to act.
02 / HOW IT CONNECTS
Seven roles.
One dengue response.
Each role has a purpose. DHO connects the district’s information and action. Choose a role to follow its part of the story.
Reports and response, connected.
02 / 07
THE DISTRICT CONNECTING POINT
District Health Officer
DHO brings local observations, healthcare information and community participation into one district view.
- Reviews field, citizen and laboratory reports.
- Coordinates teams, hospital alerts and volunteer tasks.
- Feeds the province-wide oversight picture.
A short, interactive walkthrough.
03 / THE FEATURES
AI-led detection.
A connected response.
Explore AI-assisted detection, geospatial surveillance and seven connected workspaces—built around coordinated public-health action.
Access with a purpose
Dedicated sign-in and role-based journeys give each participant their own workspace.
Identity & role accessThe provincial picture
District oversight, centralized surveillance views and resource visibility for the PHD tier.
Provincial dashboardDistrict action, connected
Reports, mapping, interventions, chemical inventory, hospital alerts and local assignments.
DHO command centreA traceable workflow
Audit records and exports make operational activity easier to review and share.
Audit & accountabilityCommunity participation
Citizens report concerns. Volunteers submit task evidence for DHO review and certificates.
Citizen & volunteer participationEvidence from the field
Camera-led reporting, GPS locations, report history and dispatch notices in a mobile-ready workspace.
Field surveillance & geo-taggingHealthcare readiness
Hospital bed and platelet updates help districts understand capacity alongside incoming alerts.
Hospital capacity & alertsLaboratory evidence
Dedicated test-record submission and tracking bring laboratory information into district review.
Laboratory recordsAI-assisted larvae recognition
Our trained image model distinguishes Aedes larvae, Non-Aedes larvae and non-larva images to support expert review.
Trained image modelEarlier outbreak warning
Early outbreak prediction brings historical dengue cases and environmental signals together for district-level risk forecasting.
Next phase · LSTM forecastingMeaningful surveillance indices
House, Container and Breteau indices turn complete inspection records into a clearer view of local breeding activity.
Inspection-based surveillanceWeather as useful context
Temperature, rainfall and humidity add environmental context to the district surveillance picture.
Environmental contextA wider view of standing water
Satellite imagery extends surveillance to larger potential standing-water habitats and environmental patterns.
Next phase · satellite intelligenceSeven connected portals and a trained image model power the project today. LSTM forecasting and satellite analysis are the next phase.
GEOSPATIAL INTELLIGENCE
See the hotspot.
Focus the response.
Explore the app’s own GIS interface: field-report markers, dashed surveillance zones, source filters and report details.
Field reportSurveillance zoneClick a marker or ring to inspect its details.
Real portal component and street map. The public example uses the location shown in your supplied screenshots; it does not expose live private records.
Open GIS image04 / INSIDE THE PLATFORM
Real screens.
Purpose-built workspaces.
Choose a role and browse the real portal tabs directly below. Open the full-size screen only when you want a larger view. Records and forms stay view-only.
01 / 07One province.
EXPLORE THE REAL INTERFACE
PROVINCIAL OVERSIGHT
One province.
A clearer picture.
The PHD workspace brings district information into a centralized view for oversight and resource visibility.
- Centralized and district views
- District and inventory management
- Mapping, audit logs and data export
Provincial Health DepartmentINTERACTIVE · VIEW ONLY
Swipe the role list to explore all seven.
2023—2027
ISLAMABAD
BUILT WITH PURPOSE
05 / ABOUT THE PROJECT
A student project.
A public-health purpose.
We’re a Computer Science team at Air University, Islamabad, united by a simple belief: better-connected information can support better-coordinated dengue prevention.
Dengue Guard AI connects seven role-specific workspaces with trained computer vision, geospatial surveillance and a vision for early prediction. Our collaboration with the District Health Office, Islamabad, keeps real public-health coordination at its centre.
Trained AI. Connected action.
Field evidence, district coordination and healthcare readiness—together in one platform.
UNIVERSITYAir University, Islamabad
DEPARTMENTComputer Science
BATCH2023–2027
FOCUSSurveillance & prevention
FORMAL PUBLIC-HEALTH COLLABORATION
A shared purpose.
A documented commitment.
In collaboration with the District Health Office, Islamabad.
The signed coordination letter supports Dengue Guard AI through proposed data access, strategic guidance and epidemiological data verification. It connects our academic work with the needs of public-health teams.
ISSUED BYDistrict Health Office, Islamabad
DATED5 March 2026
REFERENCEDHO/ICT/2026/Uni-Coord/301
06 / THE PEOPLE BEHIND IT
Three minds.
One shared purpose.
Developed at Air University, Islamabad, with guidance from our supervisor and a shared commitment to useful public-health technology.
Muhammad Farhan Afzal
Computer Science · Class of 2027
Muhammad Ahmed
Computer Science · Class of 2027
Muhammad Saad
Computer Science · Class of 2027
GUIDANCE THAT MAKES A DIFFERENCE
Dr. Maryum Nisar
Final Year Project Supervisor · Air University, Islamabad
07 / LET’S CONNECT
A healthier future
starts with a
conversation.
Interested in a platform walkthrough, public-health collaboration or research partnership? We’d be glad to connect.
iamfarhanafzal204@gmail.comConnect on LinkedIn Air University, Islamabad, PakistanYOUR QUESTIONS, ANSWERED
A clearer picture.
What does Dengue Guard AI bring together?
Seven connected portals bring provincial and district health authorities, hospitals, laboratories, field workers, citizens and volunteers into one coordinated dengue-surveillance workflow.
How does AI help identify mosquito larvae?
Our trained image model distinguishes Aedes larvae, Non-Aedes larvae and images that do not contain larvae. It supports surveillance and expert review; identifying Aedes does not mean a mosquito is infected with dengue.
What can I explore in the portal gallery?
Switch between seven real portal interfaces and use their own navigation, tabs and filters directly on this page. Open full-size screen gives you more space. The isolated public copy uses view-only example records and never connects to private accounts.
How does GIS mapping support a faster response?
The app maps geo-tagged reports as clickable markers and dashed surveillance zones. Source and risk filters help officials focus their review. Click a marker to inspect the location and report details, just as in the operational interface.
What is the vision for early prediction?
Move dengue prevention from reactive to proactive. The next phase combines LSTM-based forecasting and satellite intelligence with the connected surveillance platform, supporting earlier district-level warning and a wider national vision.
How is the District Health Office involved?
The District Health Office, Islamabad, has issued a formal collaboration letter supporting the project through proposed data access, technical guidance and epidemiological data verification. Read the signed letter in the collaboration section.
Read the coordination letterCan I install the website on my phone or computer?
Yes. Use the install button in a supporting browser to keep this website as an app. On iPhone or iPad, use Safari’s Share menu and Add to Home Screen. Your saved showcase can also be viewed offline.