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Serbian MachineCanSee on why computer vision may be the future of transportation

Serbian MachineCanSee on why computer vision may be the future of transportation,
Image credit: MachineCanSee
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What will happen when machines become advanced enough to track and predict every human action? The omnipresent machine sounds like a concept from Orwell’s 1984, but in reality AI technology is quickly developing to make more and more complex deductions from observations about human behavior and interactions. One of the businesses developing advanced technology in the field is the Serbian startup MachineCanSee. 

The Recursive talked to its founders to find out how computer vision and AI can change industries like transportation or retail.

MachineCanSee is based in Novi Sad. It was founded in 2019 by serial entrepreneur Vladan Damjanovic and Srdjan Vukmirovic, an Associate Professor at Faculty of Technical Sciences at the University of Novi Sad. The startup is focused on developing a surveillance camera technology that is better than traditional cameras and relies on AI to make smart predictions and generate data analytics. 

The idea for the company solution came from Damjanovic’s previous experience with developing computer vision aimed to automate parking. In August 2020, the company managed to raise €79.9K in its pre-seed round, led by Innovation Fund Serbia. Since then the startup has been working on developing a prototype of the AI-powered camera. 

Technology of this type is already being implemented by big companies such as Bosch, whose security and surveillance cameras perform anonymous face analysis, acknowledging age, gender, and emotions of visitors.

Currently, the teye Surveillance solution of MachineCanSee is able to detect and recognize objects at a maximum distance of 100 meters, thus seeing 4 times farther than standard cameras, and processing and analyzing data 24 times faster than an ordinary camera. The company is developing in three directions: 

  • Creating a new generation of safety cameras 
  • Facilitating the establishment of more accurate parking occupancy systems 
  • Developing AI technology that can analyze cashiers and customer interaction. 

Predicting road crashes and transforming customer experience

The parking spot occupancy solution of MachineCanSee relies on real-time occupancy information from its AI-driven sensors. It can cover up to 300 parking spaces with a single camera. The technology takes into account the car type and size to detect suitable parking spot locations and makes smart predictions derived from historical data. The cameras also have solar-powered hardware, so you don’t have to power them externally.

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The second vertical at stake for the company – the teye Driving Cam – is capable of predicting road crashes, detecting risky driving through real-time chauffeur and road monitoring. With the help of forward and backward cameras and accelerometers for erratic movement capture, the system is able to detect and warn drivers of dangers on the road through voice alerts inside the cabin. The system also detects risky behavior of the driver in cases of unsafe or aggressive driving and speeding, driver fatigue, and distracted driving. According to preliminary tests, the system will be able to detect up to 85% of road crashes. It can also save as much as 20% in fuel and maintenance costs, as the teye Cam captures and stores vehicle acceleration data that can be used for creating a more efficient driving strategy. 

MachineCanSee is also working in the smart retail sphere. The cashier and customer evaluation solution of the startup observes the interaction between clients and employees by analyzing their facial expressions, speech, and natural language of both parties. Incorporated in a 360 dual-lens camera, the AI sensors monitor and store information about different employees, creating statistical overviews and databases on how different behaviors affect customer satisfaction. The aim is to help managers increase customer satisfaction and their revenues. The final evaluation is then based on the duration of the interactions, the facial expressions, and the attentiveness of employees, as well as how friendly and responsive they are.

What about privacy?

The advancements in surveillance AI however have social implications and pose a serious concern for privacy violations. The social credit system of China, being among the most striking examples,  tracks every citizen and ranks them based on their behavior and actions. 

Vukmirovic and Damjanovic explain that all their solutions are to be GDPR-compliant. Тhey analyze the image in the camera and reduce it before it leaves the device. It only extracts information about the emotions of customers and makes deductions about the performance of a particular employee. The co-founders point out that the initial idea behind the solution is to help managers boost the productivity of their employees by registering the presence of a communications problem and understanding its origin. 

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What is next for MachineCanSee

The 2021 goals of MachineCanSee include launching the teye Camera prototype and installing the first pilot. The two founders are also planning to proceed with fundraising in the US, as this is where their business network is. The company team will also work in close partnership with Serbian universities and other institutions. Last week, MachineCanSee announced being accepted to participate in the X-Europe Smart Cities and Sustainability program as one of the 27 startups selected in the fourth cohort of the accelerator.

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Viktoria is an Innovation Reporter at The Recursive and a sophomore-standing student at the American University in Bulgaria. Combining her Business Administration studies while mapping the Southeastern European startup ecosystem is a positive-sum game for her as she has the chance to interact with the most active entrepreneurs in the region. Her favorite topics include venture capital structures, investments, as well as innovations in the scitech and fintech sectors.