Helping forest officials efficiently manage their workload

Thumbnail image for the Yaanai case study. The image contains a mobile phone mockup that has the home page of the Yaanai app. The page has google map with multiple pins to highlight each place within a larger region. There are cards at the bottom of the screen with names of the places marked in pins. The place names are in the language Tamil.

Project details

Role

Product Designer

Duration

5 months

Industry

Productivity

Team

Team of 5 undergraduate students

Responsibilities

Field research, UX/UI Design, User testing and Development

Overview

Gudalur, a region in India, is home to approximately 30,000 residents and a diverse wildlife population, notably featuring elephants. The forest officials in this area safeguard these elephants from poachers while ensuring the safety of the locals. A typical day for them involves monitoring and reporting details about elephant herds in specific regions twice a day and alerting residents about elephant movements when elephants approach human habitat areas.

Challenge

Manual logging of elephant counts poses challenges in storing and accessing information. Additionally, alerting people about elephant movements often took too long, endangering the safety of residents in some instances.

Target group

Users Icon
Forest officials
Higher authorities responsible for deciding what, when and how to alert the locals.
Users Icon
Forest rangers
Individuals who monitor elephants daily in the field and report them to the officials.
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Residents
Local residents of the region.

Approach

The journey began with on-field research, during which our team observed, immersed, and interviewed people from the surroundings. Once we gained sufficient insights into the situation from the perspectives of the rangers, officials, locals, and other user groups, we conducted an affinity diagramming workshop. This workshop included a few selected representatives from all user groups to organize our research findings and identify themes and opportunities.
An image of an affinity mapping diagram with various categories such as ‘Morning Routines’, ‘Mobile Usage Routines’, ‘Alerting System’, and others. Each category is accompanied by color-coded sticky notes detailing specific aspects or issues. The title ‘Affinity Mapping’ is displayed at the top.

Problem

Our research findings highlighted major challenges for the officials while alerting the locals, tracking elephant movements, and managing their workload overall.
01/
Inefficient alerting process

Alerting users about elephant movements involved multiple decision-makers before reaching locals in the affected region. In addition, the outdated SMS alert system required a dedicated operator, incurring additional costs and substantial delays in message relays. Moreover, in the absence of the operator or due to maintenance issues, alerting had to be done manually, with officials and rangers physically informing residents.

02/
Limited reporting platform

Relying on WhatsApp for reporting elephant movements posed challenges in promptly accessing specific information. Updating details only during sightings left gaps, requiring officials to search through attendance ledgers during those periods, which was cumbersome and risked inaccuracies, especially if ledgers were missing.

03/
Unsafe work environment

Forest rangers faced challenges even with bright long range flashlights during nighttime hours. Despite the presence of cameras, live replays were impractical due to the large data size, making wireless relay to the control room difficult. Physical card readers were employed as a workaround to store live recordings and reviewed weekly to gather insights into elephant movements and behavior.

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Goals

Reduce the number of steps in the process of alerting the locals

An efficient system to log and access information for the rangers and the officials

Solution

Observing users using the app helped us refine solutions to best fit their needs and situations during specific actions. We employed the Impact Effort Matrix to prioritize features for each phase of the long-term project.
An image of a flowchart comparing the ‘Existing way of alerting the locals’ to a ‘New way of alerting the locals’. The flowchart outlines steps and decisions in connected shapes. The existing method involves multiple steps and intermediaries, while the new method is more streamlined and direct, triggering immediate evacuation and involving Quick Response Teams (QRTs) at different stages.
Comparison between the old and new methods of alerting locals in the event of elephants being spotted near a residential area.
Fast, streamlined alerting process

The 'Yaanai' app, accessible to locals, rangers, and officials, is a centralized communication platform between all the user groups. Anyone within the range can report elephant sightings to the key decision-maker—the forest official. The official validates this information and broadcasts the alerts to locals in the specific region from the app. Users have different hierarchies and permissions aligned with their real-world chain of command. This structure prevents the dissemination of false information and facilitates effective decision-making.

An image showing three smartphone screens displaying an application interface for enhanced data management in elephant monitoring operations. The first screen shows a Google Map with various markers and place names. The second screen displays a form titled ‘Yellamalai West’ for logging data about elephants in that region. The third screen, titled ‘Report by date’, provides options for exporting data as a report.
Portal for the rangers to report their findings and for officials to export the data, presenting those findings to their higher officials.
Enhanced data management for efficient operations

All records, including details about elephant movements and rangers’ attendance, are organized and can be logged and accessed by date, place, and time. Google Maps with live location allows rangers to report more quickly and accurately. Structured data enables forest officials to promptly export and present critical information as reports to their superiors.

An image showing a camera mounted on a tree in a lush green forest, used for the automated surveillance of elephants. The camera, housed in a rectangular box-like structure, is attached to the tree using straps.
Surveillance cameras, already in place on the trees, are used to learn wildlife behavior by reviewing the footage on a weekly basis.
Automated surveillance with repurposed cameras

Spotting elephants is set to be automated by repurposing existing cameras. Although these cameras cannot transmit a live feed to the control room, a plug-in Raspberry Pi computer attached to the camera will handle the data processing, allowing real-time detection of elephant movements and triggering immediate alerts to the forest rangers.

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Arrow icon to emphasize the element along with it as a link or button

Results

A two-day camp was organized to educate officials and selected locals about the app's functionalities and usage. Support for regional language on the app made it easy for the users to follow and take action. The app has significantly reduced the time and cost of managing and reporting data for the officials.
Collage of two images. In the left image, three young adults are demonstrating the use of an app to a forest official, with various papers and mobile devices spread out on the table. The right image shows the same group outdoors, proudly displaying a camera prototype and the mobile app, representing the final outcome of their efforts.

Key takeaway

Living with the people in the environment greatly facilitated our empathy with the users, enabling us to identify the best-case solutions for them. Additionally, speaking their regional language provided an added advantage, allowing us to gather more meaningful and qualitative data from locals and officials.

Next steps

While the current prototype shows promise in detecting elephants, the implementation and testing in the environment are pending as it requires specialized professionals and incurs additional costs, pushing it to the project's next phase.

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© Murphy Caxton 2024
Logo for the name of this portfolio candidate "Murphy Caxton". Logo is a mix of the letter M & C.
© Murphy Caxton 2024