Technological advancements deployed to enhance road safety and efficiency gather a significant volume of data. This practice raises concerns among data privacy advocates around the potential misuse of such collected information. A recent example of this technological application was apparent in the case of an unfortunate hit-and-run incident involving an 81-year-old woman from St. Helena, California. Authorities employed a network of cameras reading license plates, identifying a suspect and ultimately making an arrest after a week-long investigation.
The conversion of vehicle number plate data to actionable intelligence was made possible by FLOCK’s automatic license plate reading camera system. This system scans and stores license plate numbers in a cloud-based databank. FLOCK’s product portfolio includes cameras, drones, sound detection devices, and software tools that are employed by law enforcement agencies, city administration, and schools with an aim to expedite crime resolution.
While the method of using license plate numbers to identify offenders is not novel, the autonomic collection and systematic organization of such data marks a significant stride in technological innovation. This evolution is largely attributed to the burgeoning domain of the Internet of Things (IoT), a web of connected objects that can autonomously share and receive data.
These IoT devices, commonly known as ‘smart city’ tools, are increasingly adopted by cities striving to enhance their public services, including road safety and efficiency. With intensified usage of such devices, accurately tracing the path of every citizen becomes a reality, akin to a form of GPS tracking.
The general public is quite accustomed to security cameras and traffic light detectors. However, advancements in cloud technology and artificial intelligence have enabled more extensive data collection. The resulting troves of data are analyzed, allowing strategic maneuvers to augment city services.
However, this increase in observation, data collection, and subsequent analysis also ignites the debate surrounding ethical and privacy issues. While public surveillance to verify the authenticity of a vehicle or its status may not necessarily raise eyebrows, the permanent storage of such data and its unregulated use could infringe on privacy rights.
As IoT devices become more densely integrated into our daily lives, and with at least three of them permeating every city block, it’s akin to a GPS tracking everyone. This development not only sparks policy deliberations but also raises concerns pertaining to constitutional issues.
Citizens of St. Helena in Napa Valley are likely not disturbed by the tech’s application in the aforementioned hit-and-run case, considering its effective utility. Usually, smart city technologies such as cameras and sensors record and sort data into databases using AI. These tools track safety parameters in pedestrian lanes, monitor vehicle speed, and guide traffic through intersections during peak hours.
Several interconnected systems are often referred to as intelligent transportation systems (ITS). Some can even detect traffic collisions, prompt EMS responses, and assist ambulances in reaching the accident site more promptly by controlling traffic signals. These technical systems monitor without the need for police officers patrolling throughout the roads.
IoT technologies primarily function in two methods — either via infrastructure or mobile devices. Control over the device often influences privacy implications. For instance, cameras or sensors mounted on traffic poles, or automated license plate readers, may not necessarily involve an opt-in process from citizens. But they are being employed in different regions on a case-by-case basis.
The absence of federal regulation over data privacy in traffic surveillance often leaves decisions in the hands of county or local governments. Cities and towns widely differ. All intend to procure benefits for their communities, but sometimes they may lack comprehensive understanding of the technology, which might result in some inadvertent actions.
A case in point is the city of San Diego. Since 2016, the city has installed smart streetlights with license plate readers to deter crime. Yet, the lack of clarity seemingly prevailed about the potential usage of collected data. This situation reignited privacy concerns and sparked fears of data sharing with third parties.
Eventually, the police started leveraging the cameras as surveillance tools to combat crime. This led to allegations of privacy infringement and racial targeting against the initiative. Following a budgetary review, the program was discontinued, only to restart with camera installations in 2024. The crux is proper usage of the system ensures community benefits.
A situation from Detroit underscores the importance of using the data responsibly. A woman was erroneously arrested in a drive-by shooting case. A search was conducted for white Dodge Chargers, instead of a specific license plate, which led to her identification through the cameras near her home. It highlights the necessity for federal guidance on data privacy regarding smart cities’ systems.
Without a standardized legislation, cities are left to define their own regulations. Collaborations with private tech companies for such initiatives often involve a bid process. The dynamic nature of surveillance and privacy in the digital age requires continual reassessment. Until a nationwide standardization law is passed, states are left to decide their practices keeping community needs and privacy considerations in equilibrium.