After seeing massive success as part of the second edition of the competition, Defence Research and Development Organization (DRDO) has launched the third edition of its innovation contest, 'Dare to Dream 3.0' as a tribute to the visionary, the legendary former President and eminent scientist, Dr APJ Abdul Kalam . Dr. Kalam first espoused the vision of self-reliance and India's very own development model. The Contest is being launched for promoting research in various fields of emerging technologies in order to promote both individuals and startups for the creation of innovation in defence and aerospace technologies in the country for realizing the vision of an 'Aatmanirbhar Bharat' given by our Hon'ble Prime Minister Shri Narendra Modi.


Objective: The objective of Dare to Dream 3.0 is to provide the right platform to the nation's innovators in order to unearth & realize their disruptive ideas and concepts in different disciplines of emerging technologies possessing military and dual-use identified by DRDO for enhancing defence capabilities.

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List of Areas for the Contest:


    In the modern world threats from Chemical, Biological, radiological, nuclear and explosive (CBRNe) has become reality. The emergency arising out of such event can result in injury, illness, or loss to life and property. The emergency management requires efficient and quick response to any CBRNe events. Major challenges lie in the detection of event, its location, identifying effected zones, planning evacuation routes, protecting essential services from such hazards.

      1. Design and development of a system capable of detecting hazardous material (chemicals, aerosols, bioagents etc.) in the environment and localising its point of release (source).
      2. Classification of the nature of hazard.
      3. Chemical Hazard Prediction Software.

      Early Warning and Advanced Response System (e-WARN) systems has been developed by DRDO. The hazardous contaminants (mainly B&C) are detected within the air duct. Necessary filtration and protection system gets activated on sensing the threats. It purges any percolated contaminants and makes it safe for occupants. The range of detection is very short and has very less response time.

      1. Detection range for threats due to CBRNe to be increased.
      2. Peripheral CBRNe monitoring systems may be developed
      3. Suitable LIDAR based system for detecting source of threat and its classification may be developed
      4. Chemical hazard prediction software may be developed for real-time threat assessment and activation of e-WARN system.
      5. Necessary hardware and software to be proposed
      1. Classifying/Identifying the nature of threats at a distance for activating the e-WARN protection system.
      2. Accuracy of the Hazard Prediction Software
      3. Low False Alarm.

      Timely activation of e-WARN System on detection of CBRNE threats by remote detection and thereby protecting the life and material from the hazardous environment.


    To enhance the underwater communication capability between divers, ships and submarines, there is a requirement for the development of an indigenous Underwater Diver Acoustic Communication Equipment (UDACE) for Marine Commandos. To make the equipment more tactically useful and to enhance the spectrum of operation where it can be utilized, this equipment needs to be compatible with the Base Transceiver Station (BTS) on board submarines/surface ships

    Indian Navy is presently using hard-wired mode for diver communication, where the number of communication channels & distance are limited, along with hindrances to movement of diver. A wireless mode of communication provides more flexibility to the diver and ease of deployment. Hence it is required to develop a state-of-the-art wireless Underwater Diver Acoustic Communication Equipment (UDACE) that is compatible with the Base Transceiver Stations (BTS) on-board submarines/surface ships.

    The equipment should be: (i) easily attachable to any mask; (ii) should be able to fully integrate into an existing diver communication suite; (iii) it should be equipped with an emergency mode of communication to alert other divers and base stations in case of distress; (iv) A mechanism to measure and communicate the heartbeat of the diver to base stations as a basic health monitoring system. In addition to the normal voice mode of communication, there is a requirement of throat microphone, (‘laryngophone’ that absorbs vibrations directly from the wearer's throat by way of single or dual sensors worn against the neck).


      The equipment a compact and portable unit for fitment on diver’s suit made for carrying out underwater missions. The specifications for Underwater Diver Acoustic Communication Equipment (UDACE) are:

      S.No Parameters Specifications
      1 Mode of Communication Wireless, Full Duplex
      2 Operating modes Telephony mode; Emergency mode for transmitting SOS signal; Heart beat monitoring mode
      3 Modulation schemes Single sideband Suppressed carrier Amplitude modulation in STANAG 1475(NATO)/ EKM standard (Telephony mode); Emergency Pinger & Morse code of SOS signal
      4 Power 5Watts
      5 Maximum depth of operation 80m
      6 Working Distance 500m to 1000m
      7 Battery life About 6 hours
      8 Accessories Diver Headset; Push-to-talk (PTT) Buttons; Sensitive vibration detecting microphone laryngophone (Throat Mic) with finger PTT/ bone-conduction microphone
      9 size Compact and portable unit for fitment on diver’s suit- both combat and normal suits.

      The present Diver Underwater Communication System (DUCS) mostly uses a hard-line system which utilizes the “four-wire approach” even though wireless systems are available. It is a closed loop comparable to a telephone system. A typical hard-line system consists of: (i) surface intercom; (ii) head set with boom microphone set up for four wire; (iii) diver microphone/ear phone assembly; (iv) mask microphone and full-face mask; and requires a physical connection between the listener and talker. The signal travels over the communication rope.

      Four wire communication is defined as a duplex communication route. Two wires provide the up–link signal path and two additional wires provide the down-link path. This allows everyone to be online simultaneously similar to a telephone conference call.


      The system should use advanced state of the art technology which enables the diver to use the system completely hands-free to communicate with each other and to any compatible base station equipment for various platforms. There should be provision for automatic gain and squelch control which leaves the diver hands-free for the duration of the dive. More focus is to be on the development of throat microphone which is designed to pick up (transduce) the vibrations of the vocal apparatus at the throat instead of the vibrations of air molecules at the mouth. It improves the intelligibility of voice by eliminating the noisy ambient conditions. Throat microphones make contact with the soft tissue of the throat and record vibrations from throat. It is also advisable to study the effects of bone-conduction microphones in addition to throat microphones, and compare the results and accordingly modify design of the system .


      The process of talking in underwater is influenced by the internal geometry of the life support equipment and constraints on the communications systems as well as the physical and physiological influences of the environment on the processes of speaking and vocal sound production. The use of breathing gases under pressure or containing helium causes problems in intelligibility of diver speech due to distortion caused by the different speed of sound in the gas and the different density of the gas compared to air at surface pressure. These parameters cause loss in intelligibility of sound. Also, during exhalation, more bubbles are created. Bubbles create noise, which deteriorates the quality of the sound by creating vibrations and sounds that drown out your speech. So, it is a great challenge to devise a mechanism towards the realization of a reliable Underwater Acoustic Diver Communication Equipment.


      To use in military underwater scenario as a means to provide acoustic communication link for marine commandos to other commandos and to any compatible base station equipment of various platforms.


    A smart battery is a battery with an embedded microcontroller, built-in sensors and a means to display or communicate battery status information. This configuration is manufactured as an integrated battery unit delivered to the user ready to communicate with a host system. Sensor plays a crucial role in Smart Battery thus high sensitivity and best accuracy sensors offer the possibility of "smart batteries". The field of battery sensing is moving beyond the proof of concept and is becoming crucial to the design and monitoring of smarter batteries. Master wireless communication between sensors and an advanced BMS relying on new AI protocols to achieve a fully operational smart battery pack. Sensing and self-healing functionalities are intimately linked. The vision of smart batteries integrates both these functions. Signals from the sensors will be sent to the BMS and analysed; if problems are determined, the BMS will send a signal to the actuator, triggering the stimulus of the self-healing process. This technology shall ultimately result in consistent quality, high reliability, long endurance & safety.

    Sensors that can measure with great accuracy multiple parameters such as strain, temperature, pressure, electrolyte concentration, and gas composition and can ultimately access SEI dynamics must be designed/developed. For successful implementation of the sensing tooling in a practical battery, sensors will have to be adapted to the targeted battery environment in terms of electrochemical stability, size, and manufacturing constraints, including recyclability

    Self-healing mechanisms can be classified either as autonomous or non-autonomous depending on the need for external stimulus. In general heat, light, and pH are considered as external stimulus. In both cases the components of the healing process need to be highly reactive to achieve fast and efficient reactions with solid surfaces. For this reason, very few self-healing approaches within the battery field have yet benefited from the general strategies and formalisms well established for human bodies. Copying nature’s strategy, i.e., relying on the use of sacrificial weak bonds for self-repair, battery scientists have developed molecules – polymers – with intrinsic self-healing properties based on dynamic supramolecular assembly, such as hydrogen bonding, electrostatic crosslinking, and host–guest or Van der Waals interactions Functionalised and flexible polymers that are chemically compatible with battery components have been developed, with reactive species produced in the material in response to damage. Another self-healing approach, so far barely applied in the battery community, uses microcapsules hosting healing species. These need to stay active upon their release, which is triggered by a stimulus. A plethora of self-assembling materials and bio-inspired mechanisms pertaining to the field of supramolecular chemistry and biology have also been tested to exploit radically new smart functionalities for either intrinsic or extrinsic

      1. To develop a smart battery with increased safety, highly reliable, improved cycle life batteries by introducing smart sensing and self-healing functionalities which can operate in a broadcast mode or in a data on-request mode or a combination of both which shall contain the essentials parameters like Voltage, Current, Temperature, State-of-Charge, State-of-Health, No. of cycles, Cycle Fading, Cycle Life, Endurance, etc.
      2. The developed smart battery shall also be capable of performing the spatially and temporally resolved monitoring of changes detrimental to battery life.

      The technology is at a Proof of Concept stage currently.


      The purported technology is a new emerging technology

      1. Highly Challenging due to Complexity in SEI and Electrochemical reactions
      2. Auto repair and auto recovery
      3. Development of Self-healing Electrolytes
      1. Batteries used in Military Vehicles
      2. Missile Batteries
      3. Batteries used in Military Onboard Systems

In this 21st century age, data processing capability with huge storage capacities and computing resource capabilities is definitely a must for any organisation. Cloud computing transforms the workplace into plug and play kind of environment where the end user doesn’t need to install or maintain the resources on their premises but extract all the benefits equivalent to having them at their desk.

Cloud computing is on-demand access, via the internet, to computing resources - applications, server, data storage, development tools, networking capabilities, and more -hosted at a remote data center managed by a cloud services provider.

Cloud computing is a big shift from the traditional way businesses think about IT resources. Here are

  • Lower IT costs: Cloud lets you offload some or most of the costs and effort of purchasing, installing, configuring and managing your own on-premises infrastructure.

  • Improve Agility and time-to-value: With cloud, DRDO can start using enterprise applications in minutes, instead of waiting weeks or months for IT to respond to a request, purchase and configure supporting hardware, and install software. Cloud also lets certain users- specifically developers and data scientists – to help themselves to software and support infrastructure.

  • Speed: Most cloud computing services are provided self service and on demand, so even vast amounts of computing resources can be provisioned in minutes typically with just a few mouse clicks, giving businesses a lot of flexibility and taking the pressure off capacity planning.

    The AI cloud, a concept only new starting to be implemented by enterprises, combines artificial intelligence ( AI ) with cloud computing. Two factors are driving it: AI tools and software delivering new, increased value to cloud computing which is no more just an economical option for data storage and computation but playing a significant role in AI adoption.

    An AI cloud consists of a shared infrastructure for AI use cases, support in numerous projects and AI workloads simultaneously, on cloud infrastructure at any given point in time The AI cloud brings together AI hardware and software including open source to deliver AI software- as-a-service on hybrid cloud infrastructure, providing enterprises access to AI and enabling them to harness AI capabilities. A significant amount of processing power is required to run AI algorithms, making it unaffordable for all DRDO Labs to have it, but this deterrent is being eliminated by the recent availability of AI software-as-a-service, on the lines of software-as-a-service or infrastructure-as-a-service by a centralized cloud service. The most compelling advantages of AI cloud are the challenges it addresses. It democratises AI, making it more accessible. By lowering adoption costs and facilitating co-creation and innovation, it drives AI-powered transformation for various DRDO Labs. It eliminates the need for lab-centric procurements of hardware and lab-centric maintenance costs and overhead.

    The cloud is veritably becoming a force multiplier for AI, making AI-driven insights available for everyone. Besides, though cloud computing technology now is far more prevalent than the use of AI itself, we can safely assume that AI will make cloud computing significantly more effective.

    AI-driven initiatives, providing strategic inputs for decision-making are backed by the cloud’s flexibility, agility and scale to power such intelligence massively. The cloud dramatically increases the scope and sphere of influence of AI, beginning with the user enterprise itself and then in the larger marketplace. In fact, AI and the cloud will feed off each other, aiding the true potential of AI flower though the cloud.

    The pace of this will depend only on the AI expertise that DRDO Labs can bring to bear in their workplace activities, for the cloud is already here and seeping everywhere. Investments enterprises making in using AI will gain multi-fold returns through the cloud, this makes the AI cloud very alluring.

    Inherently AI workloads are computing and memory intensive, be it training new models or running existing models. Workloads for video, speech or large text data need huge memory and processor footprint that can be easily provisioned with cloud scaling resources in an automated way. All DRDO Labs and MoD clients like the armed forces can benefit from these AI services, solutions with access to curated datasets, trained models, and an end-to-end tool stack.

    Organisations like DRDO need to build an enterprise-grade AI platform strategy with a software stack bringing together multiple technologies and stitching things together in a systemic manner to scale AI adoption.

  1. Introduction

    Cognition is formally defined as follows:

    A conscious mental activity that informs a person about his or her environment. Cognitive actions include perceiving, thinking, reasoning, judging, problem solving and remembering. Cognitive sensor technology heavily relies on statistical learning. Considering the highly complex sensor operational environment, cognitive techniques in signal generation, processing and classification have attracted the interest of the research community and have become active areas of research.

  2. Desired Outcomes and Expected Benefits:

      To build models, prototypes, simulators, development of algorithms, appropriate software modules/hardware modules to demonstrate the functionality under investigation.

    2. Recent Trends/Status of Technology

      A lot of research is going on in the field of knowledge based adaptive threshold detector, NCTR, tracking, multi-sensor data fusion, sensor ECCM.

    3. Technology Enhancement and Improvement Expected

      Knowledge based adaptive threshold detector for heterogeneous sensor environment, Non Co-operative Target Recognition (NCTR), knowledge based tracking of highly manoeuvring targets, knowledge based sensor resource management for optimum utilization, Game-theoretic approach to sensor ECCM, emitter data de-interleaving approaches for highly dynamic emitter emission characteristics in passive sensors, knowledge driven threat assessment and war strategies, design of knowledge based sensor waveforms, knowledge based antenna beam former are a few possible areas of investigations.

      The algorithms would aid in improving sensor detectability of targets under hostile emission conditions, against heterogeneous interference background. Tracking of targets could also be improved by using an effective knowledge-based sensor resource manager and target specific kinematic models. NCTR feature would aid in this process. Knowledge based de-interleaving techniques aid in emitter localization in passive sensor systems. The fire control ability also can harness the knowledge-based threat classifier for better utilization of fire power.

    4. Challenges

      The key to success in any knowledge-based system is in identifying the features, descriptors driving the logic in knowledge-based processor. This require experience and theoretical understanding in the area of investigation.

    5. Application

      Knowledge based systems find their application in almost all types of sensor system such as surveillance, imaging, tracking, fire-control, multi-static, passive etc.

  1. Introduction

    Shock wave, like an ordinary wave, carries energy and can propagate through a medium but is characterized by an abrupt (nearly discontinuous) change in pressure, temperature (or internal energy), density and entropy of the medium. Shock waves move faster than the speed of sound, so the medium ahead of the shock cannot respond until the shock strikes. Hence, the shock wave falling upon the particles of the medium is a supersonic ‘hydrodynamic surprise’. Shock wave imparts a velocity to the medium particles, through which it is traveling.

    The advancement of High-Speed Diagnostics is key technologies that heavily determines the progress of shock wave physics. There are various techniques which are utilized to study the shock wave phenomena such as high speed streak camera, shorting pins, ionization pins, piezo-resistive gauges, electromagnetic velocity gauges, and optical techniques. The Measurement of shock wave parameters lead to the detailed descriptions of material behaviour under shock wave loading. The pressure measured will be in the range of few kilobar to about 500 kilobar with time duration in microseconds range. It is relatively easy to measure the detonation velocity, but this is not the case for detonation pressure. Detonation pressure is indirectly calculated from the detonation velocity measurements.

    The development of indigenous techniques to measure pressure-time profile and free surface velocity (particle velocity) during shock wave propagation in reactive and non-reactive media will be very useful.

  2. Desired Outcomes and Expected Benefits
    1. Scope of Work

      Development of high speed diagnostic tool to measure shock wave pressure-time profile in reactive and non-reactive media

      1. Design and development of sensor/gauge to measure pressure-time profile of shock wave in reactive and non-reactive media
      2. Calibration of the pressure sensor/gauge (10-500 kbar)
      3. Development of high-speed data acquisition system compatible with the pressure sensor
      4. Record the pressure-time profile in actual experiments and validation of the results

      Development of a technique to measure free surface/particle velocity

      1. Design and develop a system to measure the free surface/particle velocity
      2. Calibrate the system with the existing data
      3. Development of compatible high-speed data acquisition system
      4. Record of free-surface velocity in actual experiments and validation of the results
    2. Recent Trends /Status of Technology

      Pressure – Time profile:
      Manganin pressure gauge has been widely used for pressure measurements of shock wave in condensed matter and detonation in condensed explosive. However, recording time of manganin gauge is limited to a few microsecond. This short recording time is not long enough to measure detonation pressure of non-ideal explosive which has long reaction zone length. For this, PVDF gauges are used which has longer recording time as compared to manganin pressure gauge. Researchers have recently used Optical Active Method (OAM) technique based on bare PMMA optical fibers (250 µm diameter) and their radiation transmission loss when shocked, was used to characterize the detonation wave and shock wave in inert barriers and applied to measure the detonation pressure in condensed explosives.

      Free Surface/ Particle Velocity:
      Free Surface and Particle Velocity of the meterials under shock is determined by using VISAR (Velocity Interferometer System for Any Reflector). It is a time-resolved velocity measurement system that uses laser interferometry to measure the surface velocity of solids moving at high speeds. For solids experiencing high velocity impact or explosive conditions, VISAR plots the free-surface velocity against time to show the shock wave profile of a material.

      Another technique used to determine velocities is Photon Doppler velocimetry (PDV). It is a one-dimensional Fourier transform analysis of a heterodyne laser interferometry, used in the shock physics community to measure velocities in dynamic experiments with high temporal precision.

    3. Technology Enhancement & Improvements Expected

      Pressure – Time profile:
      Pressure – time profile is very crucial for design and development of systems based on new explosive compositions. Need of the hour is to develop techniques which can measure the direct pressure time profile upto 500 kbar for the duration of multiples of microseconds.

      Free Surface/ Particle Velocity:
      Free surface and particle velocity are important parameters for development of high explosives as well as systems based on such explosives. Tools are required for measurement of free and particle velocities in the range of 1 – 2 km/s. Challenges

      1. The detonation pressure of condensed explosives is in the range of hundreds of kilobars, and its direct measurement is therefore difficult to perform.
      2. The sensing elements and measurement systems should be rugged field deployable and able to withstand the harsh environment of strain and temperature.
      3. High accuracy and fast response of the sensors and data acquisition system
      4. Precise alignment of optical and optoelectronic components, in case of optical methods
    4. Applications
      1. These novel diagnostic tools will help to gain a deeper understanding of shock wave studies.
      2. These techniques will be useful in the design of experiments and the interpretation of experimental data
      3. Measurements of pressure-time profile and free-surface/particle velocity are very important parameters to design a shock wave based system.

    Future warfare is going to depend heavily on drones and unmanned systems. Recent surge of drones with explosives is an indication of this trend. In recent Azerbaizan-Armenia war, the weaponized automated drones flew and attacked any human or battle-tank present down below. Powerful Armenian army suffered heavy losses due to this. Our neighboring countries are also trying to perfect the Drone attack technology to cause heavy damage on our important installations and army units. Low cost of drones, their small sizes, several possible shapes, capability to fly from anywhere and unmanned operations are key capabilities making them the most potent weapon in future. Addition of automated object recognition capability has made the drones capable of operating in remote areas inside enemy countries even if the areas are jammed from receiving any electromagnetic signal from host. Further, Face Recognition technology on these drones can enable them to attack particular persons and endanger VIP security. Collaborative Intelligence can further sharpen Drone capabilities. Even if one drone is destroyed, it can pass on information to other drones following them and they can keep attacking till their mission gets completed. The small automated drones need not always attack while flying. They can also sit somewhere and blast themselves when they find the situation suitable to do so.

    We need potent technologies to counter this menace. Problem is the small sizes of the Drones. Also, Drones can take many different shapes like birds etc. Drones can attack individually or as a team forming Drone constellations. Hence, efficient automated EO surveillance against drones and systems to automatically neutralize this threat are required to be evolved. Vast technology studies like Artificial Intelligence, Fuzzy Logic, Artificial Neural Networks, Genetic Algorithms, Ant Algorithms, Collaborative Intelligence Algorithms, Evolutionary Intelligence, Target Tracking Algorithms and studies on various sensors like electro-optical day cameras, thermal imagers, image intensifier tube based night vision cameras, radars, MMW sensors, laser sensors will be required to develop potent Anti-Drone systems.

    The proposals shall include practical studies on automated detection of drones in day/ night conditions. Machine Learning based classification of Drones and bird images can also be presented. Simulation of different Drone attack scenarios and their counter strategies can also help.

    Soldier as a system is used to improve the soldier’s capabilities in order to accomplish the assigned tasks in CI/CT operations to fight against terrorism. Soldier as a system includes subsystems like Head up displays, Battlefield Management System, Smart light weight small arms and/or weapons, protective wears, helmets etc. It is required to optimize/minimize the total weight being carried by soldiers and still provide efficient protection and information required for carrying out assigned tasks and increasing lethality, survivability and mobility of infantry soldiers.

    1. SCOPE OF WORK :
      Scope of the work involves providing conceptual design and/or prototype of HUD and BMS syb-systems that will be used to augment with other existing protection systems to enhance the capabilities of the soldiers. Linking the wearable devices with the battle management system.

      1. Digital army program launched by many countries including UK, Israel, India etc
      2. Reducing weight of the soldier as a system
      3. Ballistic helmets and advanced bulletproof vests
      4. Open architecture soldier systems
      5. Use of AR and VR
      1. Very good 3D HUD hardware systems
      2. HUD Software for displaying various types of information to soldiers like 3D maps, navigation information, Local situational awareness, information about team members and enemy location.
      3. Cordless secure communication in noisy environment
      1. Providing protection using body armor, NBC protection, helmet etc in a minimum amount of weight
      2. Providing high bandwidth communication and computation for visualization, navigation situational awareness, BMS connectivity etc
      3. Providing High endurance equipment with minimum weight.
      4. Providing good HMD display
      1. To improve the capabilities of the soldier in carrying out CI/CT operations
      2. Provide situational awareness
      3. Provide body protection
      4. To aid in decision making

    Standard imaging systems, such as cameras, radars and LIDARs, are becoming a big part of our everyday life when it comes to detection, tracking and recognition of targets that are in the direct line-of-sight (LOS) of the imaging system. Challenges however start to arise when the objects are not in the system’s LOS, typically when an occluder is obstructing the imager’s field of view. This is known as non-line-of-sight (NLOS) and it is approached in different ways. The ability to image objects outside the direct line of sight of a camera would enable applications in robotic vision, remote sensing, medical imaging, autonomous driving and many other domains. For example, the ability to see hidden obstacles could enable autonomous vehicles to avoid collisions, drive more efficiently and plan driving actions further in advance. Non- line- of- sight (NLOS) imaging goes one step further by analysing light scattered from multiple surfaces along indirect paths, with the goal of revealing the 3D shape and visual appearance of objects outside the direct line of sight.


      Development of Non Line of Sight Imaging System prototype based upon transient imaging and comprising of pulsed laser source, femto second time- resolved detectors such SPAD and image reconstruction using inverse problem


      Over the last few years, various approaches addressing the NLOS problem have been proposed. Some of these focus on advanced measurement systems, using femtosecond and picosecond time- resolved detectors, interferometry, acoustic systems, passive imaging systems or thermal imaging. Others explore models of light transport that make certain assumptions on the reflectance or other properties of the hidden scenes.

      1. Development of high sensitive and very high frame rate SPAD and array of detectors for such application.
      2. Development of image reconstruction Model

      NLOS imaging poses several challenges:

      1. Few recorded photons carry the information necessary to estimate hidden objects. Whereas the photon count of light directly reflected from a single scattering point falls off with a factor proportional to the inverse of the square distance, the signal strength of light scattered from multiple surfaces decreases several orders of magnitude faster. Robustly detecting and time- stamping the few indirectly scattered photons in the presence of the much brighter signal returning directly from the visible scene requires single- photon- sensitive detectors with a high dynamic range or with gating capabilities.
      2. Inverse problem of estimating 3D shape and appearance of hidden objects from intensity measurements alone is ill- posed. Solving the NLOS problem robustly requires advanced imaging systems capable of picosecond- accurate time- resolved measurement, mathematical priors on the imaged scenes, or other unconventional approaches.
      3. Inverse problems associated with NLOS imaging are extremely large. Developing efficient algorithms to compute solutions in reasonable times and with memory resources available on a single computer is crucial to make this emerging imaging modality practical.
      1. Autonomous driving
      2. Collision Avoidance
      3. Defence & security
      4. medical imaging
      5. Agriculture

Staying true to the words of our visionary, the late former President ,Dr APJ Abdul Kalam , who once said that one must “have courage to think differently, courage to invent, to travel the unexplored path, courage to discover the impossible and to conquer the problems and succeed”.

The open category under Dare to Dream 3.0 is to enable such innovators to exercise their courage and come up with ideas that can explore the unthinkable and unimaginable. It is designed to ensure that ideas that can provide a military advantage in the foreseeable future are given the support they require, along with support from technical experts and guidance from research stalwarts and the end users.

As part of the Open Category submissions, we believe that no innovation must be limited by the categories that we have set as part of the Contest. It invites ideas for innovations that, even though cannot be pigeonholed into any of the other technological areas, still hold enough disruptive potential to kick start and lay the foundation of defence technologies that can dictate the future as we know it.

Unlocking the right potential idea can transform the dynamics of the strategic competition in defence technologies, where the challenges in the sector are increasingly becoming more complex, unpredictable, and diverse, reflecting multiple focus areas. Under it, a submission for a development of futuristic technology in a key thrust area may be submitted for consideration by the expert panel. Under the open category, the only limitation for an innovator is their own creativity, giving them a blank slate to give life to their ideas and visions.