ElephantEdge Competition to Save Elephants and a Chance to Win Prizes up to $ 5,000
Hackster

ElephantEdge Competition to Save Elephants and a Chance to Win Prizes up to $ 5,000

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Hackster -أحد مجتمعات Avnet- هو أكبر مجتمع مطور في العالم للتعلم والبرمجة وبناء الأجهزة مع أكثر من 1.4 مليون عضو و 24 ألف من المشاريع مفتوحة المصدر. من التعلم الآلي والحوسبة المتطورة إلى أمان إنترنت ا
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DÉTAILS OPPORTUNITÉ

Organisation à but non lucratif
Date limite
16 oct. 2020
Niveau d'études
Type d'opportunité
Pays éligibles
Région éligible
Toutes les régions

Hackster.io and Smart Parks are inviting app developers around the world to participate in an elephant tracking collar competition, which can help park rangers reduce animal loss from illegal ivory poaching, trophy hunting, human conflict, and environmental degradation. With #ElephantEdge, they’re calling on the community to build ML models using the Edge Impulse Studio and tracking dashboards using Avnet’s IoTConnect, which will be deployed onto 10 production-grade collars manufactured by their engineering partner, Institute IRNAS, and deployed by Smart Parks.

Building machine learning models:

Build ML models with Edge Impulse that will be used for collar deployments. These new models will create a new Human to Elephant Language, powered by TinyML, that will help conservation efforts:

  • Poaching Risk Monitoring: Build models that can identify an increased risk for poaching. Example: Know when an elephant is moving into a high-risk area and send real-time notifications to park rangers.
  • Human Conflict Monitoring: Build models and dashboards that can prevent conflict between humans and elephants. Example: Sense and alert when an elephant is heading into an area where farmers live. This collar could detect human presence by scanning if any mobile phones or WiFi hotspots are near, by tapping the available radio modules (Nordic Semiconductor nRF52840, NINA-B30x BLE, Semtech LR1110).
  • Elephant Musth Monitoring: Build models and dashboards that can recognize when an elephant bull is in musth (a periodic condition in male elephants characterized by highly aggressive behavior and accompanied by a large rise in reproductive hormones). Example: Utilize the motion and acoustic sensors to discern this state of erratic, loud, and aggressive behavior.
  • Elephant Activity Monitoring: Build models and dashboards that can classify the general behavior of the elephant, such as when it is drinking, eating, sleeping, etc. Example: Detect and report the elephant activity by using accelerometer data. Or go more advanced and use a water detection sensor to see when the elephant goes swimming, drinking, or digging for water.
  • Elephant Communication Monitoring: Build models and dashboards that can listen for vocal communications between elephants via the onboard microphone. Example: Use sound-recording technology to listen to their vocalizations. Here's how.

Tidbits to think about:

  • Elephants are afraid of bees.
  • Elephants speak with their feet and have poor hearing.
  • Elephants radiate excess heat away from the body using their ears.
  • Elephants contribute to seed distribution.
  • Elephants perform funerals-like rituals.

Building IoT tracking dashboards:

Build an IoTConnect dashboard that will be used for collar deployments and help park rangers, track, monitor, and get on-demand alerts that are critical to conservation efforts:

  • Simulate dashboards that track location and leaving protected areas.
  • Build dashboards that report the frequency of entering high-risk areas.
  • Monitor and infer active period vs. resting period for the elephants.
  • Simulate alerts when activity deviates from the expected range.
  • Alerts to replace batteries or when a collar malfunctions, goes offline.
  • Design and ideate any other telemetry data and inference.

The new collar will use the following hardware and software:

  • Nordic Semiconductor nRF52840 Bluetooth 5, Thread, and Zigbee multi-protocol SoC.
  • u-blox NINA-B30x BLE module and ZOE-M8G GPS/GNSS module.
  • Taoglas low-power wide-area (LPWA) antennas.
  • Western Digital Edge SDSDQAB-016G microSD storage.
  • Semtech LR1110 ultra-low-power LoRaWAN transceiver.
  • STMicroelectronics LIS2DW12 ultra-low-power high-performance three-axis MEMS accelerometer, with configurable single/double-tap recognition, free-fall, wakeup, portrait/landscape, and 6D/4D orientation detections.
  • STMicroelectronics LSM303AGR ultra-compact high-performance eCompass module, with a 3D digital linear acceleration sensor and a 3D digital magnetic sensor.
  • STMicroelectronics MP23ABS1 high-performance MEMS audio sensor with single-ended analog bottom-port microphone.
  • IoTConnect Platform for dashboard creation of asset tracking.
  • Edge Impulse Studio TinyML modeling software.

Notes:

  • You do not need any hardware to build the ML models. Use datasets to sample, analyze, and build your TinyML models. You can also use your mobile phone to run simulated data collections and deployment.
  • You do not need specific hardware to build the dashboards. Use any hardware you already have, from Arduino to Microchip, Seeed, Adafruit to STMicroelectronics, to send data to the IoTConnect platform.

Prizes:

All winners will have an opportunity to showcase their projects on Microsoft IoT Developers’ Project 15 YouTube Channel in an ElephantEdge feature deep-dive video!

Top 5 Tracking Dashboards:

  • $500 value.
  • Apple Watch 3 + Custom tee. Must use IoTConnect.

Top 5 Machine Learning Models:

  • $500 value.
  • Apple Watch 3 + Custom tee. Must use Edge Impulse.

About Hackster:

Hackster, an Avnet community, is the world’s largest developer community for learning, programming, and building hardware with 1.4M+ members and 24K+ open source projects. From machine learning and edge computing to IoT security and automation, Hackster is the leading place where exploring tomorrow starts today. Hackster teams up with local and global corporate sponsors to host contests where participants can submit their inventive technology solutions for a chance to win big prizes.

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