How Device and Human Generated Data Impact Public Safety Response

Phone connected to smart objects

Effective Emergency Communications Center (ECC) response requires accurate and relevant information provided logically to achieve comprehensive situational awareness. Suffice to say, this is highly difficult during times of duress. Fortunately, the last few decades have seen drastic improvements in technologies that augment human data from assistance requests (e.g., received during 911 calls) with device-generated data. 

In this article, we'll explore how device and human-generated data influence response times and explain the pros and cons of each data type. We'll then explain how each falls short of providing the necessary detail level and context for optimal public safety response, plus how the two combined provide the required visibility and awareness when responding to emergencies.

Types of Device-Generated Data

Device-generated data is automatically created by any number of monitoring systems, surveillance devices, IoT sensors, and more. Some of these systems continuously monitor the local environment, while others may be consumer devices attached to their owners. For example, physical security systems come in the form of breakage detectors (e.g., glass), point of entry breach detectors, smoke/heat detectors, fall detection solutions, and panic buttons. Consumer health devices such as the Apple Health informatics mobile app — in conjunction with health monitoring devices such as the Apple Watch — can also provide critical health data for contextualizing response efforts.


Other common device-generated data sources include:

  • Emergency SOS apps: These features allow Apple & Android users to contact emergency services with the press of a button, either passively or actively. They can also work with other device applications to share medical information, notify emergency contacts, and other critical information about the individual.
  • Gunshot detection: These systems are deployed in high-risk environments and provide location and timestamp data when gunshots are detected.
  • Vehicle telematics systems: Because today's vehicles are highly connected, data regarding occupant/passenger safety, airbag deployment status, speed, and any crashes/collisions is automatically generated and can be used in emergency response scenarios.
  • Traffic/weather cameras: Signaling devices positioned strategically in the environment can provide critical data regarding traffic volume/density, pedestrian activity, and current weather conditions.

How does that device-generated data meet or fall short of ECC needs? 

Device-generated data often lacks complete information, may be generated from multiple sources around the same incident, and location data is not always provided with the notification. Organizing and determining what information is applicable can be time-consuming and difficult to share with others. Aggregating these data feeds into a common operational picture (COP) while using AI/ML helps determine what data is applicable and how it is displayed, whether automatically, manually, and for what purpose. The combination of multiple data sources in this manner equips professionals with the applicable information needed to provide the appropriate response to requests for emergency services.

Device data from legacy systems versus cloud-based data

Since legacy systems are typically siloed, users must access multiple systems and competing user interfaces to create a unified assessment of a situation; any useful patterns in the disparate data must be discovered manually by the operator. In contrast, cloud-based systems use application programming interfaces (APIs) to consume many data types (like calls, texts, and video) from multiple sources, automating when/how emergency data and analytics are interpreted and displayed in real-time.

Types of Human-Generated Data

Traditionally, alerts and requests for assistance to the ECCs are generated via manual efforts — either by the person requiring help or a third-party individual. For example, this could be someone dialing 911 on their mobile device or sending a text message. Real-time text (RTT) has also emerged recently as another manual alternative for requesting assistance; using RTT, a text is sent immediately to the recipient (i.e., the ECC) without having to press "send." Using IP-based networking technology, the ECC recipient can view the message as it’s being typed.

In any of these cases, the process behind the creation of human-generated data is the same: information regarding the situation is passed from caller to responder, the incident/caller's location is confirmed verbally, and in some cases, a picture or video may be shared by the caller via a data connection.

How does human-generated data meet or fall short of ECC needs?

Since most calls are made via wireless devices, poor connection quality (e.g., dropped calls, unclear audio) poses challenges to voice-based emergency response efforts. Additionally, callers may not be able to communicate information clearly due to physical limitations (such as when under duress or due to language barriers).

How Both Data Types Work Together to Benefit ECC Responses

Without additional data sources, emergency response professionals must rely on callers to communicate the situation on the ground, as well as know what questions to ask and when. By integrating multiple data sources with the caller's voice communications, ECCs can equip their professionals with the necessary insights to ask additional questions that the caller did not realize was relevant or needed. Device-generated information can act as a safeguard against erroneous human information when someone is under duress or doesn’t know something. First responders are also better equipped with the situational awareness necessary to provide optimal assistance when arriving on the scene.

Comtech SmartReponse Improves ECC Device and Human Data Insights

Comtech's SmartResponse™ is a cloud-native solution that provides emergency responders access to multiple data types in a single user interface. The platform is data source agnostic, accepting inputs from call handling platforms, CAD systems, or other third-party solutions. Flexible map views with dual displays can be changed and manipulated easily, and emergency management staff can view incidents on a wide scale to gain a holistic view of events as they unfold.

ECCs require both contextual device data as well as human-generated data from voice communications to serve the community best and properly handle emergency situations. Contact our team of incident management software experts to find out how your ECC's voice and device-generated data can be integrated for more timely, streamlined emergency response efforts.

Related Posts

How Comtech Location Technologies is Addressing COVID-19

How Comtech Location Technologies is Addressing COVID-19

We are in front of a unique challenge today with the spread of COVID-19 and the subsequent impact to society. To the extent we can, we are working …
Read More
Device-Based Hybrids Solution for Mobile Network Operators in Canada

Device-Based Hybrids Solution for Mobile Network Operators in Canada

Handset-Based Location Implementation in Canada E9-1-1 Phase II location functionality has enabled accurate locations for many wireless emergency …
Read More

Subscribe to our blog for the latest news from Comtech