3AM Innovations is protecting those who protect us with technology. Their FLORIAN software platform provides first responders with an adaptive 3D toolset, designed to empower tactics and connect decision-makers. Leveraging the interoperability of IoT, 3AM continues to integrate FLORIAN with partners who can help them save lives. With decades of incident command experience and the power of artificial intelligence, 3AM is converting the organized chaos of an emergency into actionable intelligence.

In emergency situations, locating first responders within buildings is absolutely crucial to their safety. This is especially important in dangerous environments, such as burning buildings, where indoor surroundings can quickly change at a moment’s notice, and first responders can easily be trapped in the process. If the location of these first responders was precisely known while they were in the building, additional personnel or resources could be deployed to the site to assist them in dangerous situations; this could be highly beneficial to their overall safety. Because of obstruction of signals to satellites, existing location determination technologies, such as GPS, are unreliable and relatively inaccurate as a location determination method in indoor structures. Other existing systems for general indoor location tracking come with varying advantages but do not meet the demands for versatility, dependability, and accuracy essential to first-responder tracking. There is a clear unmet need for highly accurate location tracking systems for first responders, who could benefit tremendously from such technology. AdaptiTrace meets the accuracy and versatility needs demanded of a first responder tracking technology by using a combination of novel radio and robotic localization technologies for highly accurate, reliable, and versatile xyz positioning. Indoor location-tracking systems on the market today all rely on complex infrastructure that must be installed in a building prior to usage for tracking. This requirement makes these systems unsuitable for first responders, who are often deployed at a moment’s notice to buildings that almost always lack any sort of pre-existing location-tracking infrastructure. AdaptiTrace addresses this problem by mobilizing indoor location-tracking infrastructure through drone technology, removing the need for any pre-existing infrastructure in the building. In combination with drone technology, AdaptiTrace applies principles from the latest robotics localization and mapping technologies to map and track first responders’ xyz location dynamically in real-time. The AdaptiTrace system uses ultra wide-band (UWB)-enabled drone anchors, which are distributed at key locations on the target building’s exterior. First responders carry small ultra wide-band tags when they enter the building, allowing AdaptiTrace to map their position with high accuracy (a margin of error under 10 cm) in real time. AdaptiTrace achieves this high level of accuracy using calculated time-of-flight data from each UWB-reader beacon equipped on each drone. Using the time-of-flight data, it measures key distances between anchors on the drones and tags carried by first responders. Together with novel localization algorithms from onboard sensors that localize the device a firefighter carries, AdaptiTrace is able to accurately determine the xyz position of multiple first responders in even the largest and most complex indoor structures. Furthermore, AdaptiTrace’s software system dynamically generates a multilayered 2D map as a first responder moves through a building, permitting intuitive visualization and analysis of the first-responder team’s distribution within a building. Together with our first responder partners at Dekalb County Fire and Rescue, one of the largest fire departments in the state of Georgia, the team at AdaptiTrace is hard at work to develop a breakthrough solution that meets the needs of first responders across the country.

The tracking product in development by Aiki and Quantum Interface is small, inexpensive, highly accurate and due to its deployment method, easily adaptable to any building size or shape. The small battery powered devices are dropped or thrown while performing the “360 degree survey”, an existing best practice in structural firefighting. Because of this, the system does not rely on pre-deployment yet is able to be in place and operating prior to any firefighter’s entry into an IDLH environment.

BANC3 has combined UWB (Ultra-wideband) with AI-enhanced IMU motion tracking to develop a first responder tracking system that works through walls, below grade, and at long range. Our UWB tracking provides a stable reference point in GPS denied environments, offering 3D tracking under the most challenging conditions. When walls or distance make UWB untenable, our tags stream back IMU data processed by our machine learning algorithms which remove the effect of drift, noise, and error common to motion-based tracking. Our software processes the UWB and IMU input data and produces a platform and language agnostic serialized message stream with first responder position data. This published stream allows any visualization platform to subscribe and consume 3D position data, be it a local graph for engineering debug, our cloud-based first responder software, or a third-party solution. We aim to provide an open platform that allows for integrating new tracking technologies using a similar serialized messaging stream. BANC3 has already demonstrated how we can use that to include GPS data or 6DoF SLAM data from our AR headsets. We have tested our current prototype UWB, and IMU solution in a single-family dwelling and office building, both inside and out, and have seen promising tracking results. BANC3 has also spent time with our first responder partners to review our current and future system design, their needs, and how we can help meet them. In future phases of the competition, we aim to improve our accuracy and move towards commercializing our own UWB tags and integrating our software into our RespondEye system for first responders.

For first responders such as firefighters, accurate locational tracking has been identified as a critical need. In particular, knowing the exact location of individuals within an indoor structure (including the specific floor of a multi-floor building) during a search and rescue operation is vital to their safety. While GPS approaches are sufficient for many applications, it is impossible to use GPS to effectively locate people who are indoors or underground. Even in outdoor environments, there are situations for which GPS may be unavailable, such as dense urban areas where tall buildings or narrow streets can lead to “urban-canyon” phenomena. The team Business Crescendo/SYSNAV proposes to develop an accurate, real-time geolocation and tracking solution for individuals in GPS-denied conditions, including indoor structures, without any pre-deployed infrastructure. The approach involves a robust but lightweight ankle-worn tracking device which utilizes magneto-inertial technology. A notable challenge of using IMU (Inertial Measurement Unit) systems for navigation is that such systems suffer from accumulated error. Because the mathematical approach underlying IMU navigation (ie “dead reckoning”) relies on integrating acceleration with respect to time in order to calculate velocity and position, any measurement errors, however small, are accumulated over time, leading to “drift” which increases based on the distance traveled from the initial position. This team will deliver a superior realtime 3D geolocation and tracking solution, through the combination of precise magneto-inertial sensors and sophisticated algorithms, which allow exceptional performance even in the absense of maps, beacons, and GPS – although the solution can opportunistically make use digital maps, GPS, or external beacons if they happen to be available. The team has already demonstrated its ability to deliver such solutions. The team will build on its subject matter expertise and the past developments, and will work collaboratively with WFCA and other experts to leverage their input, in order to bring the solution to the next level. The overall projected solution, with its fit-for-purpose software user interface and its fast initialization procedure, will be designed with the first responder in mind. While sufficiently robust, the solution will be accurate, easy-to-use, and cost-effective. In summary, the team believes that its geolocation and tracking system, especially with the improvements envisioned over the course of this FRST Challenge program, will provide a superior solution for the needs of first responders.

Every day, First Responders intervene to save our lives. But who ensures the safety of these agents during interventions? The location of first responders is essential to ensure their safety and optimize interventions. Many needs are identified, such as the ability to find endangered officer even without visibility, tracking and monitoring agents in real time and in all environments, identification of secured itinerary, etc. However, today, no commercialized solution meets the requirements of precise and reliable tracking of agents. Nav4you and Jade Tree proposes CHARLI (CHallenging AReas Localisation servIces) project. Our solution exploits an innovative foot-mounted location device merging inertial, magnetic and GNSS raw signals with artificial intelligence and innovative algorithms. Unlike commercially available solutions, CHARLI guarantees 3D sub-meter location accuracy without the need for a ground-based beacon infrastructure. Our device provides necessary elements to localise endangered agents in real time and detect incident regardless of the environment: it works outdoor and indoor. To achieve these performances, we use innovative algorithms to benefit from degraded GNSS data even inside buildings, where it is usually rejected. The temporal difference in magnetic fields makes it possible to obtain orientation information in buildings where a traditional compass does not work. These updates, based on signal analysis, guarantee the desired accuracy in any environment. In addition, a unique artificial intelligence-based model analyzes and detects a wide variety of human movements in real time. This model is used to adapt the algorithms to the environmental and dynamic context. A complete software offer including a supervision software, an optional smartphone user app and a post intervention analysis software complete the solution. The supervision software will allow the unit leader or control team to monitor the position of individual officers in real-time and to be alerted in case of an incident. The smartphone user app will allow the user to benefit from navigation services in some situations and the post-intervention analysis software will allow scenarios to be replayed and interventions to be optimized. Our solution is developed in partnership with professional firefighters in order to meet their specific requirements in the field. Thus, the constraints of cost, size, weight and resistance are integrated into the project. The solution is resistant, lightweight and easy to use. The problem of information transmission in underground or built environment is also addressed, thanks to the use of a low frequency RF communication gateway. However, our solution is also capable of communicating via Bluetooth and Wi-Fi, which allows the use of opportune signals when they are available. Nav4you is a spin-off of Geoloc laboratory from Gustave Eiffel University in France. The Geoloc laboratory, thanks to its involvement in a large number of international research projects, has become an international reference in the field of GNSS and navigation technologies. Nav4you benefits from a great expertise in the field of indoor localisation and cartography. Its innovative device and algorithms have won multiple awards. JADE TREE is a US company specialising in the development and sale of design accessories based on acoustic and thermal innovation. We believe that our CHARLI solution will adapt to the different use cases of first responders and will save lives.

Circle Optics has developed a novel technology for multi-camera systems that provides 180° and 360° wide field of view images and data capture, in real-time and stitch-free, to enable improved situational awareness of an environment or events therein. This technology is very adaptable, and can be developed and optimized in different configurations, with single or multiple sensing modalities (e.g., VIS & IR), and be deployed across a variety of platforms (e.g., on a drone, soldier, or vehicle), and thus provide enhanced panoramic images while potentially satisfying several priorities in the current application. In particular, this application seeks improved command and control of first responders that may be distributed across indoor environments, by converging data from multiple domains and enabling rapid understanding of changes in remote environments. Circle Optics proposes a real-time image capture solution using photogrammetry with distributed or moving sensors to create digital twins of remote environments, thus enabling both command and control and first responders to have a shared common operating picture of the environment.

We propose a system of anchors and tags to identify and report the 3-dimensional location of First Responders and other assets in an indoor incident area. Anchors are hand-deployed as needed during an incident and tags are equipped on First Responders and assets. All components are battery powered, and mesh networked to the reporting device, thus requiring no on-site infrastructure – such as electricity or cellular service – to deploy and function. Existing electronic maps for the incident, while optional, are useful for the deployment of anchors and the visualization of location. The main deployment advantage of this design is that the system can be deployed dynamically and flexibly with no planning. The mesh networking used in deployment is exceptionally pliable and user friendly. Tags/anchors are located in 3-dimensions to an accuracy of 30cm by using Ultra Wide Band wireless radios to calculate Time-of-Flight ranges from each tag to the constellation of anchors and then triangulating its position. Each anchor is also located in relation to each of its neighbor anchors. The location and orientation of the resulting constellation is wholly defined by the establishment of a ‘base-plane’ (2d), or a ‘base volume’ (3d), for completely self-referential tracking. Such plane or volume is easily established during setup. This ability for a first responder to dynamically place anchors, as they move through the building and without significant loss of accuracy, is seen as a significant advantage in a rapidly changing circumstance such as a fire or related emergency. Koliada is an experienced embedded devices and IoT engineering firm with product successes across many fields including industrial, mining & medical devices, traffic safety, toys, and consumer goods. Its particular expertise in wireless technologies makes it perfectly suited to addressing the First Responder Smart Tracking Challenge. Our approach to user experience design and ruggedization is user-driven design iteration. We also have prior experience ruggedizing IoT products for roadside and athletic use. With our first responder partner, the FRST community, and others, we will be getting feedback on our design sketches and prototypes to flexibly and rapidly arrive at forms best suited to physical trials and eventually the market. We are exploring two directions for the design of the tag, worn by first responders - either about the size of a bottle cap, which can be integrated with existing kit such as a radio; or larger, rugged and easy to remember to attach to outfit. This is from feedback working with first responders; however, the fundamentally small size of our electronics gives us plenty of flexibility. Our design for the anchor, deployed by first responders at the incident, is about the size and shape of a baseball. It’s important for the anchors to be compact so that first responders can carry enough of them (likely 6 per person depending on the incident) to deploy accurate tracking. We will be building our smart tracking solution on Koliada’s embedded system SDK, which allows for rapid and robust software/firmware prototyping and extensibility through pre-designed modular hardware components, and for cost-effective commercialization through low resource requirements, simple reduction to manufacturing, and supply chain flexibility. We will develop basic visualization software to pair with our location solution, while focusing on interoperability with other visualization and situational awareness solutions.

Situational Awareness is paramount during an emergency situation. It helps to provide safety to the first responders who are selflessly providing safety to others. Currently this situational awareness comes at the cost reduced cognitive capacity due to the need to manually communicate and track each person’s location. First responders are forced to resort to rudimentary tactics to achieve this situational awareness. Locations are often verbally communicated and tracked manually on white boards or paper. This not only takes focus away from the dangerous task at hand, but is also prone to error in the chaotic nature of an emergency situation. This proposal aims to create a solution to address the need for tracking first responders during an emergency response. Specifically, it presents an ad-hoc network of ultra-wideband (UWB) devices to ascertain the location of each first responder and communicate that information back to a centralized command center monitored by an onsite director. From there, the onsite director can help navigate first responders away from dangerous areas, locate an incapacitated team member, or even ensure that all personnel have been evacuated at the conclusion of the response. UWB uses short pulse sequences, called burst pulse modulation, to transmit data as opposed amplitude or frequency modulation used in most RF applications. Due to this mechanism, communication is not restricted to any particular radio frequency, allowing it to operate over a wide band (which is where the name is derived from). Timing between UWB pulses is exceptionally small (2 nanoseconds) and benefit from very clean “edges,” allowing for precise determination of a signal’s arrival. Using these high precision timestamps and the known speed of light, relative distances between objects can be very accurately calculated. Utilizing ultra-wideband technology creates the potential for a system that can track a first responder within 10 centimeters. As with many technology development projects, we have more unknowns than knowns when we start. It is not until we actually begin experimenting and building the technology that we understand what truly provides the most value to the mission. For this reason, this system will be created utilizing Agile methodologies for an incremental and modular approach. The team will create a backlog of potential work to be completed for each milestone, broken up into outcome oriented units called “user stories.”  These user stories are prioritized from highest to lowest in terms of the amount of potential value they contribute towards the end product.  The high priority user stories reside at the top of the backlog and consist of small digestible pieces of work that will be performed in the near term.  As you move down the backlog, the user stories become larger and more general, as they are more likely to change as we make new discoveries while building out the solution. This agile implementation will also include iterative prototyping of the final design. By doing so, the team will be able to solicit regular feedback from the first responder community after providing hands on demos. This will help to ensure that the product developed actually meets the needs of the on-site emergency responders.

NavigateIO is developing a real-time, visual, and accurate infrastructure-free location intelligence solution in 3-Dimensional space. NavigateIO works in GPS denied areas like indoors and rugged terrains and could be easily integrated with GPS enabled systems. In addition to tracking x and y-direction on each floor, the solution can also identify the floor of the first responder location. First responders are displayed with unique identifiers on the graphical user interface as separate floors for tracking purposes. Each first responder carries a wearable tracking beacon. By providing real-time situational awareness and trajectory data for digestion into different systems, NavigateIO ensures accountability of personnel and enables more efficient 4Cs (command, control, communications, and coordination) of a mission. Above results in significantly reduced response time that saves lives and properties. NavigateIO is an end-to-end system that can be deployed in an on-demand and ad hoc manner, making it perfect for real-time public safety/emergency response events. The system is portable and self-contained, so there is no significant overhead expenditure. NavigateIO is innovated by top talents in mobile wireless sensing, communication, and networking. The heart of the solution lies in intelligent sensor fusion and a unique algorithmic approach to solving this complex problem for first responders. Today, promising solutions can accurately track mobile entities indoors using visual-inertial odometry in favorable visual conditions or by leveraging fine-grained ranging (RF, ultrasonic, IR, etc.) to reference anchors. However, they cannot directly cater to "dynamic" indoor environments (e.g., first responder scenarios, etc.) devoid of favorable conditions. NavigateIO researchers have shown that the need for "infrastructure-free" and robustness to "node mobility" and "visual conditions" in such environments motivate a robust RF-based approach. Also, NavigateIO understood the need to address a novel and challenging variant of its infrastructure-free localization problem that is latency-bounded. Therefore, accurate tracking of mobile entities imposes a latency budget that affects the solution computation, and the collection of peer-to-peer ranges themselves. The design and deployment of NavigateIO address this latency-bounded infrastructure-free RF localization problem. To this end, NavigateIO unravels the fundamental tradeoff between latency and localization accuracy. NavigateIO incorporates design elements that judiciously leverage the available ranging resources to adaptively estimate the joint topology of nodes, coupled with robust algorithm that maximizes the localization accuracy even in the face of practical environmental artifacts (Wireless connectivity and multipath, node mobility, etc.). The above techniques allow NavigateIO to track (every second and improve) a network of a few tens of mobile entities even at running speeds with a median accuracy of a meter level currently and without infrastructure support. NavigateIO team is working hard to improve the above performance metrics with the constant refinement of the solution. NavigateIO team also understands the robustness and ruggedization needs for the harsh environment where first responders operate. NavigateIO's current prototype has held up reasonably in multiple firefighter tastings that involved working in a harsh environment. Through these learnings, our team has developed a plan to address any gaps in the durability, environmental (temperature, dust, water ingress), other anti-penetration needs, and still being able to function to meet the requirements of first responders' intelligent location tracking. Finally, the NavigateIO team has put much effort into making the whole workings and various interfaces extremely simple for first responders to keep the focus on their missions. NavigateIO has tested and validated our system in the field in different building types and environments and successfully passed various success criteria provided by first responder departments.

Urgently searching and rescuing in an unfamiliar scene could be unexpectedly dangerous for first responders, such as a team of police officers dealing with an active shooter situation or firefighters in a burning apartment. Prompt and accurate monitoring of the first responders in those scenarios is needed for them to safely accomplish their missions. It requires us to develop an intelligent 3D tracking system in assisting the responders in localizing each other. Most existing solutions need pre-installed and carefully calibrated physical sensor infrastructure which could be costly, time-consuming, or infeasible for deployment. To address the challenges above, we propose an infrastructure-independent visual localization system that combines several advanced hardware and software modules to achieve both fast response time and cost-efficiency. Our system takes advantage of multi-modal images, including RGB, thermal, and radar images, for mapping the environment and providing localization services under various challenging scenarios. We envision a two-phase process. Phase one happens before first responders enter the scene. Its goal is to rapidly capture a map of the unknown 3D environment of interest to the first responders, and when necessary, to deploy signal beacons to create a local communication network and improve future localization robustness and accuracy. This could be done by our teleoperated or fully autonomous mobile robots. For spaces that are difficult for mobile robots to enter, this step could also be accomplished or augmented by first responders equipped with wearable multi-modal cameras. These cameras are the main sensors we use in Phase two, where the 3D positions and orientations of first responders are localized and tracked in the previously created 3D map. We use the hierarchical localization strategy in our software, combining visual place recognition and visual localization algorithms that are developed and owned by our team. Our early experiments have shown that our system could achieve real-time and accurate localization with an average error of less than 1 meter in a large hospital-like indoor space.

We propose highly effective but low cost and low adoption to barrier architecture by creating a temporary LoraWan / 4G mesh network deployed on drones over the search area. 3D location of the first responder can be discovered by using radio telemetry and signal attenuation calculation of Lorawan/4G transmitter added onto first responder’s smartphone, as well as determining altitude from built-in barometers in most factory built smartphones. There will be minimal R&D effort in beginning to build the transmitter that’s suitable for smartphone form factor, but this should be relatively fast. Data can be augmented by the smart phones ability to sense the surroundings such as known wifi networks and GPS, if they are available. The smartphone app will also have the capability of sending voice / text notes over the LoraWan network in case manual communication is required. The ad-hoc deployed network is dynamic - as the data receivers are installed on the drones, and drones can be algorithmically controlled to “comb” an area until a positive identification of the transmitter is discovered. The data transmitters / receivers will be constantly broadcasting their status to each other, so real time reporting will be available. The only thing the first responders have to do is 1) install the transmitter device and 2) fire up the drone control tablet. Because of time and budget limitations of hardware R&D, testing, and deployment , we propose using off-the-shelf drones, tablets, transmitters, etc. that are already mass produced and can be easily acquired/replaced at relatively low costs. Most of the innovation will occur on the software level, where cost of iteration is in fractions and can be deployed quickly. Most of the system will be automated and requires little to no human intervention. The smartphone app and drone controlling softwares will be developed using design principles used in consumer applications that first responders are already used to. There will be little to no training involved, as most of the user interface will be familiar. Because of low cost in obtaining hardware, rapid iterative software development, and low learning curve, the solution can be used for almost all first responder situations, including police, fire, medical, military, wildlife, border control, natural disaster, etc.

During an emergency, first responders risk their lives to help those in need. Knowing the whereabouts of individual personnel and/or other deployed resources in the field is of critical importance during emergencies. If a first responder is missing and not communicative, then it is important to know where they are physically located to effectively direct resources for immediate help. Or if operators know where the personnel who are in need of assistance are physically located and any at risk responder is able to communicate, then these operators can help guide them to safety. Today’s location-based solutions are either limited by 2-D mapping or are complicated and expensive solutions to track the real-time location of a first responder. And what if the disaster or search-and-rescue missions are off the grid? We are proposing a hardware and software solution that consists of a cheap and easy-to-use mesh network and a cloud data platform. OWL developed an ad-hoc mesh network that consists of an Internet-of-Things (IoT) device called the “DuckLink” or “Duck.” Each Duck runs an open source firmware developed by OWL called the ClusterDuck Protocol (CDP). The Duck device leverages LoRa (Long Range Radio) for 3-dimensional mapping and real-time data transportation and has an array of sensors integrated to collect temperature, humidity, pressure, multiple gas exposures, and more to provide situational awareness. All these Duck devices cluster together into the ClusterDuck Network (CDN) and transport all network components’ data to one Duck Gateway where offline data can be analyzed and be uploaded to the cloud by either Wifi, LTE, or satellite. All this data is collected by the OWL’s Data Management System (DMS) where 3-D mapping tools, live data streams, and Duck/first responder's current health vitals can be leveraged to better make decisions in the field. In addition, the data streams can be integrated with existing Emergency Operations Center’s (EOC) by using the APIs and integration tools provided by the DMS. Therefore the first responders will have real-time situational awareness of the task at hand. We will develop an algorithm on top of the CDP, called the Duck Positioning System (DPS) that can estimate the location of each deployed Duck that is part of a response by creating a localized PNT (Position, Navigation, and Timing). Part of our solution is that if a first responder has a Duck (small, lightweight, and very easy to use) in their possession, the nearby Ducks can provide the information necessary for the algorithm to produce a 3-D estimate of the location of that first responder. The first response team can then utilize this location tracker and information about the environment within the immediate area in which they are deployed to make better decisions regarding deployments of resources, as well as to provide appropriate assistance to an individual responder when and where this assistance may be needed. OWL Integrations (formerly Project OWL) won the global grand prize in the 2018 IBM disaster resilience Call for Code competition from over 100,000 competitors. This competition focused on surfacing technologies that can support communities with innovative technology to help them prepare for, deal with, and recover from natural disasters. Coming on the heels of 4 major Atlantic hurricanes - Maria, Irma, Harvey, and Florence - these disasters inflicted over $300B in economic damage and resulted in 10,000 casualties. With this founding mission in mind, OWL continued to focus on the goal of disaster resilience, which effort has included the company successfully executing a WorldBank funded grant to deploy wireless communications across Himachal Pradesh in northern India in November of 2021. This fundamental technology flexibly applies to several large, multi-billion dollar markets. We are developing sensor equipment for industrial and energy sector challenges, logistics and fleet management solutions, and disaster resilience communications networks. In the proposed solution we see a huge value for the firefighter. Current communication systems are bulky and outdated and the price is high. We see a value in providing these small devices with a lower price point that add a new layer of Firefighter monitoring which does not exist to-date. We are looking to partner with firefighters, EMS and other first responders to better define the need in emergency scenarios. This solution can be applied to the Department of Defense, disaster response, asset tracking and logistics. All these markets require an infrastructure for data collection and distribution in an offline and remote environment. We have seen multiple companies develop and operate solutions in these fields but are not able to customize and adapt to all these markets at once. We choose the name OWL Integrations since we believe the key is to be able to integrate with existing solutions already deployed in the field. Instead of replacing traditional radio and communication systems, we want to add a layer of data collection for these challenging environments.

PicoTags are a dynamic set of intelligent system nodes that provide integrated location services for humans, machines, sensors, and other resources. The system incorporates self-healing and self-configuring internetworking and fusion of location information even in the harshest conditions. The capabilities leverage the Pico Anywhere SuiteTM of interference resistant methods to ensure continuous operations even if uplinks, networks, clouds, or other enterprise systems are not available. PicoTags provide assured location services where and when you need it, even for worst day scenarios and conditions. Pico systems are built for Extreme IoT to provide comms, collaboration, applications, sensors/IoT, location services, and AI/ML at the edge within constrained, degraded, and often disconnected conditions. The Pico system, which is embedded within the PicoTags, provides a P2P and Mesh system for continuous operations and real time self-healing anywhere – including metal rich, concrete, forest, fire barriers, electrical interference, and other austere situations that emergency responders find themselves in. The system is self-reliant and scales from two nodes to thousands of nodes without dependencies on any outside networks or clouds to provide full operational support and location services within the local area when there is degradation, disconnects, disruptions, or inadequate uplink connectivity. Pico is COTS-based with open standards to allow for full interoperability across multiple radio, cellular, FirstNet, SatCOM, and other network uplinks. Further Pico’s Open APIs provide seamless integration into regional systems, enterprise systems, and cloud services, including local to regional to global CivTAK rapid integration for on-the-go collaboration and comms. The location services we aim to advance within this project will be easy to integrate into any user interface or command operation application you desire. PicoTags location services will provide a variety of methods where each node provides GPS and non-GPS location information. The native Pico location service techniques can be combined with other existing or 3rd party location services techniques where Pico’s AI-based location algorithms provide location service fusion to increase accuracy, data quality, and other sensor fusion to ensure location and status are available per human or machine responder. The core Pico technology underlying the PicoTags has successfully been field tested in high interference conditions with humans, UAVs, UAGs, large and small equipment, and other resources and tools. The system is flexible and lightweight to allow for wearable and mountable options, along options to integrate other sensors (e.g., exposure monitoring, health monitoring, etc) if desired to reduce the amount of electronics and battery load for responders. As such PicoTags location services for this project will address location services anywhere or provide a system that helps consolidate and integrate other wearable systems on responders to increase situational awareness and command/control locally and at operation centers. Overall, PicoTags has the potential to augment existing location services, integrate with other 3rd party location services, and/or provide a redundantly indestructible set of location services for any pack and go scenario responders encounter, especially in harsh situations of buildings, underground conditions, disasters (where other comms out), in cyber threatened conditions, and even in challenging fire situations that disrupt many types of communication networks.

Pierce Aerospace proposes a concept to rapidly deploy commercially available high quality sensors to an incident commander through a pre-approved identification and tracking mechanism (Remote ID) actively in development for the commercial and civil identification and tracking of unmanned aircraft systems (UAS). In the near future numerous commercial UAS with high quality sensors will be operational over airspace all across the nation. These sensors provide tremendous opportunities for utilization of first responders, but those UAS and their operators must first pass through an approval process to be granted access to airspace overhead of an emergency. Pierce Aerospace’s Flight Portal ID (FPID) technology suite is a collection of technologies designed to positively identify, authenticate, assure, and verify the identity of an individual piloting a UAS. This technology is designed to meet the requirements of the FAA for their Remote ID and Tracking Rule - which requires nearly all UAS pilots in the United States to equip their aircraft with a local broadcast Remote ID capability. This effectively puts a digital license plate on every drone. This rule goes into full effect in September 2023. Commercially, this rule and Remote ID equipment lay the foundation for advanced UAS to scale for advanced flight activities, such as commercial delivery. These advanced commercial aircraft are equipped with advanced sensors, which could be utilized in emergency situations, but those aircraft need to verify their identities and credentials prior to public safety and first responders capabilities to take advantage of those sensors.

We at Rescunomics believe that the safety of the first responder is of utmost importance if any lives can be saved at emergency scenes. As first responders ourselves, we understand these pain points and we are committed to bringing innovative solutions to Global safety issues. For decades, firefighting and emergency first response has been pure grit strength and courage with limited tools to protect the rescuer during emergencies. Getting to the scene is easy with GPS navigation but we have failed to provide a pre-plan on what to expect at these scenes and when inside. Our teams’ solution finally solves this pain point by not only providing a means of tracking first responders cost-effectively without cumbersome equipment set-up but also eliminates the technological risk that a loss of power, a common event that is prevalent in these chaotic scenes, brings. Even other civilian occupants can also be tracked and rescued if they have smart phones on them. Our solution also provides first responders with a view of the interior layouts of the scene in structural firefighting; a history of that building and any modifications showing entry and egress points; hazardous contents as in the case of chemical storage warehouses. And most importantly with the push of a button, our assistive A.I. provides a security feature whereby building occupants; teachers or school administrators can send silent SOS signals in active shooter events directly to local law enforcement bypassing the traditional 911 dispatch call taker system, saving response times and lives in the process. Again, the fact that 60% of active shooter events ending before law enforcement arrives is indeed a cry for help and a call for proactive action. Victims will be able to view layout showing evacuation routes if they choose to evacuate in these chaotic events. Our solution also enables wildland firefighters to track themselves up to 30 meters in outdoor open spaces. Welcome to the future of emergency first response.

The Smart Firefighting team is composed of startups pushing innovations (SlateSafety, Longan Vision, Squishy Robotics, EaseAlert, FlowMSP, Mappedin) established industry players (3M Scott, Motorola, W. S. Darley & Co.), community builders (Make Safe Tech, Smart Firefighting) and research institution (Illinois Fire Service Institute). Together, we are building the unifying dashboard for Incident Command - providing actionable insight into firefighters' health, environment, and location during structural burns. Location tracking has been a challenge for first responders, as GPS is often not accurate enough to ascertain a person’s location or elevation within a building. A 3D tracking technology that can provide 1-meter accuracy in an indoor setting is needed for first responders. However, we believe only knowing the first responder’s location is not sufficient without the awareness of their biometric information and environmental factors. Team Smart Firefighting aims to address localization and biometric monitoring during structural burns through our complementary technology which can be customized and retrofitted onto any equipment the fire department is currently using. Ascent’s Shield Platform generates floorplans, tracks firefighters on a multiple-story building along the X, Y, and Z axes, and identifies firefighters as they enter and exit the incident. Additionally, the platform notifies the Incident Commander of detected maydays from falls or abnormalities via health and environmental alerts. The platform is compatible with all existing connected technologies on the fireground and serves as the primary tool for pre-planning as well as consolidating all the information needed for report-outs. The goal of our team is to bring first responders home safely to their families by providing biometric, environmental, and location insights to enhance interoperability and survivability. Ascent’s sensor equipment - the ShieldModule, facilitates the streaming of thermal imaging, environmental conditions, location, and mapping back to the ShieldPortal. The ShieldModule mounts onto existing Self-Contained Breathing Apparatuses (SBCAs), masks, or helmets without changing the base functionality of the personal protective equipment (PPE). Through the combined sensor input of Ascent’s sensor, the environmental conditions (e.g., environmental CO2, humidity, airborne metal oxide) and location (accelerometer, gyroscope, magnetometer, GPS, GLONASS, SBAS, WAAS, EGNOS, MSAS, GAGAN, environmental pressure, gait tracking, ML, and integration of firefighter training and behavior data) can be monitored. Through Slate Safety’s wearable, firefighter vitals (heart rate, O2 saturation, stress, body temperature), can be monitored and presented in a centralized and organized format to the Incident Command on the Shield Platform for easy asset management. The information can also be replayed after the incident for training purposes, investigation, or review by clinicians or government officials. Our technology will improve the safety and productivity of firefighters on the ground. The team’s sensor suites and portal identify abnormal heart rates, provide simultaneous localization/tracking, and notify of potential hazards before they become a more serious problem. During the product development journey, we have been actively working with our first responder partner - IFSI, to assure our solution is addressing firefighters’ specific needs during firefighting missions and the user experience is optimized for our heroes. The targeted 1-meter 3D indoor location tracking accuracy for this challenge will be achieved by 1) multiple sensor sources; 2) indoor structure mapping; and 3) machine learning model to predict indoor structure in real-time, 4) integration of first responder training and behavior data.

Of all the most challenging aspects for first responder incident commanders, maintaining situational awareness of their personnel, both inside and outside of a structure, remains paramount. This situational awareness equates to response efficiency, team effectiveness, and the overall safety of all on-scene personnel. Although a top priority of the first responder industry for decades, deployable interior tracking of first responders has remained just beyond the industry’s reach due technological limitations, prohibitive developmental and fielding costs, as well as unrealistic employment solutions. The Holy Grail of first responder technology has remained elusive until now! Rapidly evolving technology found in the fields of geospatial positioning and locating now allow for a detailed real-time view of First Responder Accountability. Since 2015, Taber Innovations Group LLC (TIG), a Nevada-based Service-Disabled Veteran Owned Small Business (SDVOSB), has been engaged with fire departments and leading industry experts across the United States in the research and development of OWL™. OWL™ offers incident commanders at all levels the ability to accurately monitor their team’s movements and location via wearable technology transmitting real time information to the incident commander’s laptop or other mobile device in their command support vehicles. Powered by their internationally patented technology stack Location-Enhanced Accountability of Personnel™ (LEAP™) technology, OWL™, TIG has successfully produced a wearable ruggedized, non-obstructive, in-line, and cost effective individual geolocating unit based on LEAP™ and developed as a core cross-industry interoperable technology stack providing pinpoint/real time location tracking data to organizations across a variety of applications to a broad spectrum of commercial and military applications. These venues include, but are not exclusively limited to, firefighters/emergency medical technicians, law enforcement officers, military units, mine/tunnel (underground) workers, health care facilities, and event venue/amusement park safety. Additionally, the LEAP™ interoperable technology stack provides cross service organizations, such as firefighters and law enforcement responding to the same incident, simultaneous precise locational situational awareness on all on-scene personnel both inside and outside of structures. OWL™ is designed as a dynamically deployable, standalone, and scalable system that does not require a costly and sensitive support infrastructure to be maintained by departments or municipalities. OWL™ is designed to be operated within a variety of austere environmental conditions with minimal to no impact on nationally accepted and adopted firefighting Standard Operating Procedures. Through the utilization of the latest in motion, positioning, and communication technologies, OWL™ provides the incident command structure, both on-scene and remote, to rapidly and accurately track the status, health, and location of personnel and equipment throughout the duration of an incident both on the exterior and the interior of a multi-story structure. OWL™ also offers data storage capability to allow for the incident debriefing and multiple training opportunities through the Visualized Incident Replay (VIR) system. As OWL™ enters the final phases of third-party testing and certification, TIG is aggressively working to field OWL™ as soon as possible to get OWL™ into the hands of incident commanders to provide them the ability to make rapid and well-informed decisions to protect the protectors by saving lives, reducing serious injuries, and getting everyone home at the end of the shift.

Team Zansors seeks to contribute to reducing the risk faced by first responders. Team Zansors proposes novel technologies to enhance situational awareness, safety and security. Team Zansors brings its prior work in patented wearable sensors and embedded algorithm technologies for health and wellness applications and now extrapolates these technologies for first responder applications. Team Zansors will customize a miniaturized device for tracking the location of first responders in building structures above ground and underground like tunnels and basements. Team Zansors will design and build a printed circuit board with multiple micro-electronics to enable real-time location and communication. Team Zansors will design and develop unique algorithms for real-time location for first responders and offer a unique display for both the first responder and incident commander. Team Zansors comprises a multi-disciplinary team of engineers (electrical, mechanical, systems), data scientists, software programmers, designers, and public emergency management professionals. Team Zansors has relationships with larger entities that can assist in commercializing the innovation.

Third Wave is a powerful internet of things (IoT) platform that enables companies to quickly and easily build, connect, and manage low-power intelligent wearable solutions. The full-stack IoT platform spans hardware, embedded operating systems, platform services, and applications. With a suite of no-code tools, users gain access to an integrated set of customizable building blocks that dramatically shorten time to market. Utilizing a combination of low-power wide-area network (LPWAN) communication technologies, sensor fusion, and edge computing (TinyML) plus ledger-based processing environments, our secure solutions enable people to be safer, smarter, healthier, and happier wherever they are. For the First Responder Start Tracking (FRST) Challenge, Third Wave’s team is leveraging their own platform and expertise to develop an end-to-end solution for the safety and health of first responders. By utilizing their proprietary combination of location, environmental, activity, and physiolocal sensors built for challenging RF and GPS-denied areas, Third Wave’s solution can support a variety of first responder use cases out of the box. Additionally, the solution uses commercially available components and market-ready technologies (i.e. LoRa) that are affordable and easy to deploy. Third Wave is excited to join the FRST challenge, yet remains open to collaboration and research opportunities that advance the safety, health, and security of people.

We improve the health and safety of first responders with technology that better tracks and accounts for rescuers throughout the entire emergency. We have developed the DoorBoss, a proprietary firefighting tool that restricts flow path, thereby limiting fire growth and helping to save firefighters’ lives and avoid property loss. We have incorporated RFID-based sensors into the DoorBoss and leveraged technology developed at The Ohio State University (OSU) to create an IoT integrated system that can track and report the location and movements of emergency personnel in real-time. The technology licensed from OSU is summarized by antenna technology which also doubles as Wi-Fi amplification is woven into the textile of the protective gear worn by the rescuer. (We have completed the proof-of-concept stage with the licensed technology and further prototyping is needed) For example, a firefighter will place the DoorBoss in a doorway or entry point as they enter a structure. The sensor in the DoorBoss will then connect to the antenna technology worn by the firefighter and recognize their movements in and out of the entry point. This information is then sent to an incident commander’s mobile device in real-time. The proposed technology will time-stamp how long a first responder has been in a hazardous environment and how long they have had to rest. Further, the first responder’s biometric information will be viewable; providing incident commanders full accountability of their personnel with a passive; hands-free solution. Our user interface is CAD integrated and can be used without the use of the DoorBoss and sensor technology. Incident commanders can use the interface as a digital accountability board allowing for pre-planning incidents, pre-loading of daily personnel and assignments, and drag and drop crews into tactical positions throughout the emergency. The drag and drop feature allows incidents commanders further assignments details within the hazard zone as well as mark incident milestones. All tactical decisions are time-stamped, archived, and pre-loaded for NFIRS reporting. Our user interface is in the proof of concept stage of development and further prototyping is needed.

WAVELET combines three novel and emerging capabilities driven by a deep understanding of neuro- cognitive decision making for first responders to deliver a first-of-a-kind standoff sensor and mapping tool to locate not just firefighters but civilians, hostages, and friendlies. Our solution will end up saving lives at an affordable price to ensure it is accessible to as many first responders as is possible. The primary sensor is a Sense Through the Wall (STTW) system by Wavsens that will provide a never before level of tracking fidelity to first responders. By combining this data with other data sets in a high-fidelity 3D simulation and rendering engine, we can apply ML and AI and fuse multiple data sources, then serve this data to whatever tools requires it, be it AI, API back to HQ, Local ATAK connection or even alerts or alarms. Our team features both firefighter and warfighter veterans and the value of the robust communications they have afforded the team to connect back to other sources or communicate to first responders inside and beyond visual line of sight (BVLOS). Connectivity allows for the dissemination of knowledge and knowing what to share when and how is critical for the commanders and responders. Finally, we have veterans of UK Firefighter Tracking competitions, neuro-cognitive specialists and, most importantly, active Fire Fighters and Veterancy of First Responders. These are specialists that understand the complexity of contemporary situational awareness. Without them we have no purpose and no problem to solve and no benefit to bring either communities: first responders or shareholders. We’re determined to relegate firefighter tracking to the annuls of Wikipedia and peer into the unknown to save lives.

Tiami Networks proposes the use of public digital TV (DTV) stations as positioning beacons for three- dimensional indoor tracking in GPS-denied environments without pre-deployed infrastructure. DTV stations provide near-ubiquitous coverage across the United States since a single high-power DTV station has a range of 35-40 miles. Our preliminary analysis shows that DTV signals have up to 1000 times (30 dB) better coverage and outdoor-to-indoor penetration compared to FirstNet cellular radio transmissions. We will develop a wearable, battery-powered DTV positioning receiver that exploits the DTV ATSC 3.0 broadcast waveform to record DTV signal strengths and times of arrival from multiple stations. The measurements are used to infer the 3D receiver location since DTV station locations and mast heights are fixed. The ATSC 3.0 waveform is similar to 5G, thus many of the signal processing techniques that provide high-precision positioning accuracy in 5G networks are reusable to attain the

TrackerDLN presents a comprehensive solution that addresses the two key technology innovations that are required for accurate 3-D geolocation services in environments where GPS is unreliable and/or not available: accurate geolocation and a reliable net-work that can relay that location to the incident command in an actionable timeframe. The core innovation of TrackerDLN is the use of Data Logistics Networking (DLN) technology, which creates an ad-hoc network that provides asynchronous, yet reliable data transfer in situations of uncertain connectivity. This assumption of little or no network connectivity means that TrackerDLN will be deployable in any type of scenario – whether that be high rise, wide rise, underground environments, or rugged terrain. Data is transferred seamlessly among devices without any action by the end user, al-lowing for locations to be transmitted back to the incident command without requiring any additional work from the first responder. TrackerDLN provides geolocation via a combination of smart sensor based dead-reckoning with location-refining measurements obtained by measuring signal strengths of the DLN network among the deployed devices. The dead-reckoning algo-rithm employed expands on current state-of-the-art services that provide accurate 2-D location to a solution that also provides a reliable vertical measurement. Inherently us-ing the properties of the underlying ad-hoc network gives a solution that becomes more accurate as more devices are deployed on the network, allowing for this solution to be used in both large and small response events. As the solution provided by TrackerDLN is inherently software-based, the system can be deployed either via custom-built hardware configurations that are easily transporta-ble or through direct integration with existing First Responder equipment deployments that are already outfitted with wifi/Bluetooth and basic compute capabilities. Hardware configurations are available in a variety of form factors to meet users’ specific SWaP requirements, including larger models that can be housed in ruggedized cases the size of a small shoe box down to smaller models that can fit in the palm of your hand.

“Mayday” is a universal distress message that no firefighters or first responders want to hear. These emergency responders use a “Mayday” message when they are trapped, low on air, and disorientated. According to the National Institute for Occupational Safety and Health (NIOSH), approximately 80 to 100 firefighters are lost in the line of duty each year. These public safety personnel often operate in very complex environments where GPS has significantly degraded accuracy or fails. Therefore, it is an immediate demand to have an accurate and robust 3D positioning system dedicated to firefighters to increase situational awareness and personal accountability. Team ZOT