Let's break this down:
- Automation is when people don't need to do them, whether the tasks are simple or hard. Once a process is set up in a program, it can be repeated as needed.
- Traditional automation requires a clear definition from the start. Every aspect, from input to output, needs to be carefully planned and outlined by a person.
- Intelligent Automation (IA) allows machines to handle both complex and simple processes without the need for explicit instructions. IAs usually use machine learning such as generator AI and natural language processing to suggest ways to analyze and take action on existing data and usage patterns.
These solutions help security operators with the right information at the right time, allowing them to focus on core activities instead of searching and analyzing data patterns.
AI-compatible technology Improve retail security
To address ORC, retail crime and reduction, today's retail loss prevention investigators may be tasked with considering hundreds of cases in various stores. They are also trying to prevent internal theft in warehouses and distribution centers. By enhancing the process and implementing better monitoring systems, it will help retailers become more resilient with these threats.
Let's explore several ways retailers can use IA to improve their safety and security strategies.
1. Empower loss prevention teams by reducing friction – When cameras are recorded during store opening hours, retailers collect hundreds of hours of video per store each week. This is a lot of data that is difficult to sift. It's not enough to collect and store the video footage. Retailers equip their loss prevention teams with tools to potentially actively use footage efficiently to deal with threats.
Rules and actions established within security systems can help reduce false alarms and reduce tension in monitoring hundreds of cameras. Automatic alerts notify operators of related videos indicating potential threats or incidents. By utilizing these computerized features, security teams can keep their focus on what's important and avoid the need to monitor all their cameras at the same time.
For example, a security system can alert operators of potential losses. This may include individuals or groups who spend a long period of unsupervised in high-value passages. Once an alert is sent to the security team, management can determine whether the area requires additional monitoring or attention.
2. Speed up investigations – AI-enabled technologies can also help post-interior research. Manually searching for video footage can take hours or days, allowing you to sapply resources and slow down your investigation. Advanced System Automation and IA can help bridge the gap between response and investigation.
Instead of scrutinizing videos for hours to find a specific clip, IA allows investigators to do so within minutes. Modern security systems feature natural language forensic search capabilities, allowing operators to quickly find the footage they need. Simply provide prompts such as “The Man in a Blue Shirt” or “The Red Truck with Box” and operators can easily see all video clips matching that search within a certain time.
Once footage is placed, loss prevention teams can use a Digital Evidence Management System (DEMS) to quickly and safely share evidence with law enforcement. All steps are done digitally, eliminating the hassle of physical copying and making collaboration between retailers and law enforcement faster and easier.
3. Vehicle license plate detection – Organized retail crime groups often target stores in a particular sector. A network of retailers within the community can install automatic license plate recognition (ALPR) cameras across locations to collectively capture data. This means that each location will track the license plates of vehicles entering the facility and have access to shared ALPR data with other participating retailers nearby.
When a vehicle tag linked to a previous theft is detected at a location, a real-time notification is automatically sent to the store, where it is flagged. By notifying partner stores about suspects, retailers can work together to work together to build stronger cases against criminals and ensure better asset protection.
More than security: Improve your customer experience
While modern security platforms with AI-enabled technologies can greatly enhance security and research, these solutions also provide valuable insights to improve operational efficiency. Retailers can correlate videos with other systems to gain insight into the customer experience. Cross-reference of video footage with heat mapping, number of people, and other analytics can help retailers understand customer journeys at checkout through stores.
This insight provides opportunities to enhance the customer experience, promote sales and manage staffing more effectively. Below are four ways retailers can deploy IAs to improve customer experiences:
1. Understanding customer flow –– Using machine learning, retailers can analyze data from in-store cameras to gain insight into walking path patterns and their variations over different days and times. This makes it easy to establish a data-driven benchmark for customer latency and point of sale (POS) for protected products. They can more effectively redistribute the most effective staff to provide a better shopping experience and greater sales.
Large coffee store chains have implemented advanced analytics to study the flow of customers and determine the optimal store layout. Where is the best place for self-service items, such as straws, napkins, sugar? What signs do you need to direct traffic? The answers to these questions helped to improve the layout of the story and overall customer experience.
2. Increase sales by rethinking displays, marketing and promotions – Motion analysis counting and direction people help retailers understand the effectiveness of store displays. Security System Analysis allows you to track how many people view the display. Retailers can compare it with POS data on the number of products on sale. Calculating the display conversion speed gives you concrete feedback and assess which approach is best.
Sales and Marketing departments can gain insight into the success of their initiatives by tracking traffic patterns in stores before, during and after promotional campaigns. They can extract annual comparisons and identify which programs accelerated traffic up to the day and time of the week.
3. Refill and cleaning prioritization –– Retailers are becoming creative about optimizing operations using video data. Video data can be used to track empty shelves and restock and sort processes more efficiently.
Video analysis can also help address the cleanliness of the store and notify staff if there are signs of a failure, such as collapsed displays or blocking store corridors or exits. Some stores deploy cameras to monitor specific areas of shelves and retail space.
4. Queue detection –– a Longlines detected in the register can alert you to management. Supervisors can reduce bottlenecks by opening new cash registers. This response can create a positive customer experience and lead to increased transactions.
Management can use technology beyond the checkout area. Monitoring zones across stores allows team members to alert customers who need help and help employees close future sales.
Adopts intelligent automation and Loop man
For most retailers, AI implementation involves several driving factors: achieving large-scale data analysis and higher levels of automation. They aim to leverage physical security investments and data to increase the effectiveness of their loss prevention teams.
With these solutions, it is essential to understand that most AI solutions in physical security are not all-rounder. AI is a critical component of reaching a higher level of automation, but many considerations, foresight, and planning are still needed to achieve accurate results.
Being careful when exploring new AI solutions is essential. AI models cannot make critical decisions themselves. When choosing new software, consider some key best practices as technology continues to evolve.
- Keep data protection and privacy in mind: Manufacturers should only use datasets that respect the relevant data protection regulations. Similarly, systems must include robust authorization and authentication measures to ensure access to sensitive data across AI-driven applications.
- fOCUS on Transparency and Equality: Find manufacturers that will rigorously test your AI models to ensure you deliver balanced, fair, and unbiased results. The results should also be accurate and explainable.
Make sure that humans have the final say: Machines cannot grasp the complexity of real-life events like security operators. AI models present data in a way that helps humans make more informed choices, but humans should always be decision makers.
