Artificial Intelligence | News | Insights | AiThority
[bsfp-cryptocurrency style=”widget-18″ align=”marquee” columns=”6″ coins=”selected” coins-count=”6″ coins-selected=”BTC,ETH,XRP,LTC,EOS,ADA,XLM,NEO,LTC,EOS,XEM,DASH,USDT,BNB,QTUM,XVG,ONT,ZEC,STEEM” currency=”USD” title=”Cryptocurrency Widget” show_title=”0″ icon=”” scheme=”light” bs-show-desktop=”1″ bs-show-tablet=”1″ bs-show-phone=”1″ custom-css-class=”” custom-id=”” css=”.vc_custom_1523079266073{margin-bottom: 0px !important;padding-top: 0px !important;padding-bottom: 0px !important;}”]

Sensormatic Solutions by Johnson Controls Expands Its Computer Vision Offering to Address Retail’s Most Pressing Challenges

  • Johnson Controls brand Sensormatic Solutions’ innovative technology architecture offers flexible, computer vision-powered analytics to facilitate next-generation loss prevention solutions, traffic monitoring, inventory intelligence and shopper behaviour activity insights

  • Real-time insights into retail-specific use cases can help leaders to make proactive, informed decisions

  • Sensormatic Solutions’ computer vision technology leverages existing video infrastructure investments and is easy to deploy

Sensormatic Solutions, the leading global retail solutions portfolio of Johnson Controls, has expanded its computer vision analytics offering, which focuses on driving sales, reducing risk and enhancing the shopper experience. The company’s computer vision solutions are created in partnership with Intel and optimised for retail using proprietary Sensormatic IQ artificial intelligence (AI) algorithms. With Sensormatic Solutions’ computer vision capabilities, retailers can leverage existing video infrastructure and a smart hub appliance to tap into the data needed to open a world of problem-solving solutions across the retail landscape.

Read More About AI News : Role of AI in Helping B2B companies that are Missing Out on Buyer Intent Data

First introduced in 2021, Sensormatic Solutions’ computer vision offering can be easily deployed using a smart hub device in conjunction with existing camera infrastructure, to facilitate streamlined, cost-effective adoption of next-generation AI in retail environments. Computer vision automates tasks and derives meaningful information from video footage in real time, helping to strengthen loss prevention efforts, provide insights on shopper behaviour and maintain safe environments for shoppers and assistants.

The flexible architecture of this solution allows retailers to tailor systems to their unique needs. Computer vision analytics can be used to address a wide range of real-world challenges, including customer engagement, stocking, labour allocation, loss prevention, shopper satisfaction and much more. Current capabilities include:

Related Posts
1 of 33,192
  • Shelf Sweep Detection: monitors shelf activity for large-scale removal of items so that in-store personnel can take pre-emptive measures to mitigate theft. Alerts assistants of low stocks and tracks the movement of high-value items that are taken from shelves.
  • Vehicle Alert: monitors car parking areas to identify unauthorised or abandoned vehicles and to monitor customer wait times in order to mitigate organised retail crime (ORC) and improve customer experiences.
  • Loitering Monitoring: helps retailers to mitigate ORC events by identifying individuals lingering in low-traffic areas after business hours, when criminal activity is more likely to occur.
  • Group Detection Alert: monitors any groups entering or forming within stores and alerts assistants to help prevent ORC events.
  • Traffic Pattern Insights: observes paths to purchase and shopper movements throughout the floor to facilitate more effective layouts, stocking and more.
  • Slip-and-Fall Detection: monitors sales floors for shoppers who may have injured themselves on the premises.
  • Audience Measurement: provides insights into shopper demographics and sentiments so that retailers are equipped with the necessary data to curate exceptional shopping experiences by tailoring marketing plans, promotions and offerings to their unique customer base.
  • Dwell Time Measurement: analyses the length of time customers spend engaging with different displays to help retailers evaluate the effectiveness of their campaigns and promotions.

AI ML in Marketing: AI and Big Data Analysis Used to Find Brands’ Emotional Connection

“We’re working side-by-side with incubator customers to identify and design timely solutions that target the most challenging retail problems; our computer vision offering allows us to solve these problems and streamline operations using existing video infrastructure,” said Subramanian Kunchithapatham, chief technology officer at Sensormatic Solutions. “The technology architecture allows retailers to add and remove computer vision analytics capabilities as needed to complement their current solutions. The latest enhancements can help retailers to learn about customer behaviour, mitigate losses and develop better shopping experiences, while also allowing them to look beyond loss prevention for video integration.”

These product enhancements come at a time when the popularity of AI-based video monitoring is growing in the retail industry. A recent study conducted by Sensormatic Solutions and Coresight found that 43% of retail leaders surveyed currently use AI to analyse in-store video, and a further 31% expect to adopt these solutions in the next 1-3 years. Sensormatic Solutions is at the forefront of this growing market and has recently been named one of Business Innovation Group’s 2022 AI Excellence Award winners for its computer vision capabilities.

Future of AI-driven Customer RelationshipMicrosoft’s Viva Sales and the Future of AI-driven Customer Relationship and Experience Management

[To share your insights with us, please write to sghosh@martechseries.com]

Comments are closed.