The potential for integrating visual data with the IoT
The IoT is already part of our daily lives, enabling us to control our heating from any location and monitor our fitness. Its potential is being explored through research projects such as the Environmental Internet of Things, which includes digital collars on sheep and rainfall and river flow monitors. These devices send their data to cloud storage, where it is combined with other data, analysed and interpreted to help manage an ecosystem for the benefit of all stakeholders, says James Wickes, CEO and co-founder, Cloudview. Meanwhile Moocall determines when cows are about to calve.
However, I believe we will only obtain the full potential of the IoT when we add visual data to create the Visual IoT (VIoT). This does not require a battalion of new digital cameras; we simply need to combine the terabytes of visual data already available with other IoT data.
Digital cameras are everywhere, from traffic cameras and CCTV systems to numberplate recognition and systems that measure how often digital billboard advertisements are viewed. At present much of the data is only used for a single purpose, and only a tiny percentage of what is collected is ever viewed.
Adding this data to that from other sources, then using predictive analytics, artificial intelligence and deep learning, could transform all aspects of our lives. Potential applications range from improving business practices to combating crime, and from preventing disease to protecting the environment.
We are already seeing companies such as Vodafone integrating cloud-based CCTV with building security systems, adding visual verification to intruder alarms. Such systems can enable home security companies and the police to check properties visually when an alarm goes off and quickly ascertain whether a break-in has occurred. This can provide significant time and cost savings while enabling immediate action to be taken if appropriate.
Another application is city centre parking. According to the British Parking Association, 30% of city centre drivers are not on their way to or from a destination but looking for a parking space. Cameras could monitor roadside parking spots, letting a central system know which are unoccupied.
Location data could be shared with a driver’s routing app, with visual data made accessible so they know what they are looking for. It should even be possible for the driver to book a space and authorise payment to be made automatically, with length of stay calculated and payment taken when they leave.
Applying analytics to visual data will lead to further applications by revealing patterns and predicting future behaviours. This intelligence will help organisations optimise systems, improve safety and make better, faster, more appropriate decisions. It can help to work out the best number and location for objects based on their use, such as calculating the optimum number of fork lift trucks needed at a distribution plant, or the best location for equipment in a hospital. The good news is that machines are doing the ‘watching’ – not people.
Cameras combined with the right analytics can be configured to map patterns of movement in real time, helping to understand the number and flow of people in public […]
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