Autonomous Modular Radar (AMR)

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Robotics and Automation are a design of machines that assist humans in a variety of fields (https://contest.techbriefs.com/contest-rules) for the application of technology, including artificial intelligence and machine learning, to automate tasks that are inefficient, difficult, or impossible for humans to perform.

To revolutionize the local defense and ensure a comfort zone for all, DSV Limited Kano is thrilled to announce the launch of a new invention, “Autonomous Modular Radar (AMR)”, a low-frequency foliate-penetrating (FOPEN) radar module. This Nigeria designed and fabricated system is lightweight and can detect bandits and Boko Haram hideouts fast before the large military equipment respond. 

This robot (ZUMA) is not a weapon, it's a trustable surveillance system designed to support security forces in front-areas, offering hope for citizens living with devastating defense challenges.

As bandits are highly mobile groups exploiting the rugged forest corridors of the Northwest, while Boko Haram and ISWAP are utilizing the vast savannahs and water vectors of the Lake Chad basin in the Northeast, this technology exhibits two (2) significant ways, in helping the struggling traditional, heavy fixed military infrastructure cover these massive porous spaces, and in order to help change the equation.

  1. FOPEN Radar ignores the leaves and reflects off solid objects moving underneath the canopy. This allows security forces to map out hidden enclaves, track the movement of bandit columns on motorbikes, and execute precision ambushes before the criminals can launch raids on vulnerable communities.

  2. Ground surveillance radar, for check-point and border monitoring to protect international borders with Niger, Chad, and Cameroon and mitigate flow of illegal arms, insurgent fighters, and movement of stolen cattle.

How Does It Work?

While Nigeria has a growing domestic defense manufacturing industry producing armoured fighting vehicles such as the Ezugwu MRAP and Proforce Ara, the country does not currently manufacture military radar vehicles. Instead, the Nigerian military mounts imported radar systems onto domestic or imported tactical vehicle platforms. This calls for a local backup to Nigeria’s airspace surveillance in addition to foreign-procured mobile units. 

The Modularity Advantage: The true value of modular radar in this conflict isn't just the physics of radio waves—it's operational flexibility. Instead of relying on a multi-million dollar fixed radar tower that becomes a target itself, security forces can move, swap, upgrade, or relocate sensor modules depending on whether they are fighting a forest-based kidnapping ring or a drone-using insurgent cell.

To produce the modular radar robots in Nigeria, DSV's model will fabricate all locally available materials, fixtures and components, then source and import necessary radar systems to be programmed within the country. 

Conclusion

This mobile modular radar can assist in a task difficult or impossible for soldiers. At DSV, we are applying artificial intelligence and machine learning to enable soldiers efficiently detect bandit and Boko Haram movements, intercepting threats and securing dangerous blind spots, safeguarding our troops.

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  • About the Entrant

  • Name:
    Uba Sani Kibiya
  • Type of entry:
    team
    Team members:
    • Uba Sani Kibiya
    • Haruna Garba Rabo
    • Ahmad Uba Sani
    • Umma Uba Sani
    • Rabiu Uba Sani
    • Usman Salisu Shehu
    • Umar Jibrin Hussaini
  • Profession:
    Engineer/Designer
  • Number of times previously entering contest:
    3
  • Uba's favorite design and analysis tools:
    AUTOCAD, SOLIDWORKS, PATENTSCOPE, ESPACENET, WORD PROCESSOR, POWERPOINT PRESENTATION, ETC.
  • Uba's hobbies and activities:
    Reading, Brousing, Footballing and Table Tennis.
  • Uba belongs to these online communities:
    WIPO PATENTSCOPE, SAE, ACS, etc.
  • Uba is inspired by:
    I learn more that what I taught.
  • Software used for this entry:
    AutoCAD and ARDUINO IDE
  • Patent status:
    pending