Railroad Tracks and Early Warning Systems
Might Sri Lanka benefit from newly developed technologies? Take a look at the field of possibilities:
Across South Asia, innovative and traditional technologies are converging to prevent deadly collisions between elephants and trains, illustrating a multi-faceted approach to wildlife conservation. In regions like Sri Lanka and India, advanced systems such as Sensonic's Distributed Acoustic Sensing (DAS) technology use fiber optic cables and AI to monitor elephant movements in real-time, alerting train operators to avoid accidents along critical railway corridors. Meanwhile, in India's Anamalai Hills, the integration of both modern and old-school methods—such as GSM-based indicator lights, SMS alerts, and local cable TV broadcasts—continues to demonstrate success. These systems not only engage the community but also blend cutting-edge AI with grassroots techniques, showing that combining innovation with simplicity can create powerful solutions for human-wildlife coexistence
Nature Conservation Foundation - India
.1. Sri Lanka's Current Situation
On October 18, 2024, a fuel train collided with a herd of elephants in Sri Lanka's North Central Province, resulting in the deaths of two elephants and the derailment of four fuel tankers. This incident highlights the urgency of implementing effective safety measures in areas where railway tracks intersect elephant habitats. Despite these challenges, Sri Lanka is exploring innovative solutions similar to those employed in India to mitigate such risks.
Sri Lanka’s ongoing challenges with elephant-train collisions, which claim the lives of around 15-20 elephants each year. While various technological measures like sensors and cameras have been tested, they often fall short due to high costs and limited reach. Potential improvements, including installing underpasses and reducing train speeds at key crossings, combined with real-time elephant tracking, as more effective long-term solutions for protecting both elephants and train operations. While radio collaring all the elephants in these areas have been considered, it’s not a realistic option as hundreds of elephants would need to be tracked and sedated, and this is dangerous for the rangers and the elephants.
2. Sensonic’s Distributed Acoustic Sensing (DAS) System in India
Location: Indian Railways’ East Coast Network, specifically across the states of Orissa and Jharkhand.
Implementation: Sensonic’s system, known as the "Gajraj" system, uses DAS technology, which monitors vibrations through fiber optic cables embedded alongside railway tracks. The AI-enabled system detects elephant movements in real-time by recognizing their unique footsteps, allowing immediate alerts to be sent to railway staff
Scale and Success: This system covers over 400 km of railway tracks across 30 critical elephant corridors. It is designed to safeguard both wildlife and train operations by enabling railway personnel to slow down or stop trains when elephants are detected. This approach has significantly reduced elephant fatalities and minimized disruptions to train schedules, benefiting both local communities and ecosystems
3. AI-based Early Warning Systems in Coimbatore, India
Location: Near Coimbatore, Tamil Nadu.
System Details: The AI-based system here utilizes thermal imaging and deep learning models to monitor elephant crossings. In its trial phase, it recorded over 150 successful detections in one month, proving its effectiveness in high-traffic corridors. This system provides instant notifications to railway staff, allowing preventive measures like speed reduction and track clearance to be implemented swiftly
4. Wildlife SOS’s Early Warning Network
Scope: Wildlife SOS, an Indian conservation organization, has deployed early warning networks in various elephant corridors, integrating AI and real-time alerts. This system is particularly efficient in regions where elephant crossings are frequent, providing crucial support to railway authorities in mitigating collision risks.
Outcomes: The program has shown considerable promise, significantly reducing accidents by offering timely alerts and allowing for safe intervention measures
5. Amrita University's Bioacoustic Monitoring System
Technology: In collaboration with local authorities, Amrita University has introduced a bioacoustic monitoring system using deep learning models to detect elephant vocalizations. This system offers a different approach by identifying the presence of elephants through sound patterns, allowing for early warning alerts even before the animals reach the tracks
Success: This method not only protects elephants but also supports broader conservation efforts by integrating AI with biological monitoring, enhancing real-time detection accuracy
6. Thailand’s AI Efforts for Elephant Protection
In Thailand, similar AI-based systems are being trialed, focusing on providing real-time alerts to railway staff. These initiatives are part of a broader effort to enhance wildlife safety in regions where railway lines intersect natural habitats
These AI-driven systems illustrate a growing regional trend towards using advanced technology to mitigate human-wildlife conflicts, particularly in protecting endangered elephants along railway tracks. Each project, from Sensonic’s DAS technology to bioacoustic models, plays a critical role in developing sustainable solutions for railway safety and wildlife conservation.
The elephant warning system in the Anamalai Hills, particularly in the Valparai plateau, successfully integrates both modern and traditional technologies to manage human-elephant conflicts. While the program uses SMS alerts, cable TV broadcasts, and GSM-based indicator lights, its continued success is also due to the application of simpler, old-school methods that remain highly effective.
Local Cable TV Broadcasts:
The use of local cable TV to broadcast elephant locations is an example of leveraging older technology to reach a wide audience. This approach ensures that even those without access to mobile phones or advanced technology receive critical information. The broadcast system is simple yet efficient, and it remains a reliable means of communication for the community
Community-operated Indicator Lights:
Another traditional aspect of the system is the GSM-based red indicator lights installed at key locations. These lights are manually operated by local residents who receive notifications about elephant movements. This method, though technologically basic, empowers the community by involving them directly in safety measures, creating a sense of shared responsibility. Such a grassroots approach combines simple technology with local knowledge and vigilance, proving that sophisticated systems aren't always necessary to achieve effective conservation outcomes
Elephant Informant Network:
The early system, initiated before the widespread use of mobile phones, relied on an elephant informant network. Local residents and tea estate workers would pass information verbally about elephant sightings, which was then relayed across communities. This network still plays a role today, supplementing more modern methods and ensuring that information reaches people through both high-tech and traditional means
By combining these straightforward, old-school technologies with newer innovations, the program in the Anamalai Hills has successfully created a comprehensive, resilient system for minimizing human-elephant conflicts, demonstrating that sometimes, the most effective solutions blend simplicity with community involvement