• Ravi Rawan

How Technology Amplifies Intelligence in Security Monitoring




Security companies with ARC (Alarm Receiving Centre) or SOC (Security Operations Centre) are not only confronted with new customer requirements and changes in technology, but also challenged by global competition leading to fundamental changes of today’s security industry.


New technologies emerging through Logistics 4.0 continue to be widely adopted and used throughout the security industry in its various forms and applications. We can agree that the technology advancements bring great benefits to the security companies. In supply chain security, technology has delivered improved connectivity, enhanced visibility, AI assisted decision making and decision tools to aid the execution of security monitoring processes. In contrast, a human intervention is the only way to truly stop theft in the progress.


 

The evolution of IOT and big data in every step of the supply chain is considerably reducing the volume of tasks which require human intervention. To prevent current and future risks, the security industry must embrace technology in order to deliver smart systems and efficient services that can produce collaborative intelligence between technology and humans. This will result in better informed decisions, actions, and recommendations, creating an outcome that is smarter, than the sum of each individual contribution.


Delivering cargo security and monitoring services since the early 90’s, GGL Security can relate to this ongoing evolution of technology in the security industry. With creation and delivery of the ALL ONE VIEW platform, we embrace this change through digital transformation to mitigate the challenges we face as a security provider.


“You can have data without information, but you cannot have information without data.” — Daniel Keys Moran.

Integrated systems and connected data from IOT systems are the key ingredients to delivering an intelligent collaboration between technology and SOC teams through a unified system. This presents a nightmarish challenge for a security company and for a 3PL trying to implement cargo security measures in their ecosystem. Typically caused by use of multiple GIS and IOT systems in the 3PL ecosystem, implementation of quality security measures on fragmented systems quickly becomes an impossible task and a burden on security and planning resources.


By utilizing the latest technological advancements in ALL ONE VIEW, we integrated fragmented systems together into one data pool for security monitoring and visibility of shipments. Driven by customer requirements, ALL ONE VIEW now has integration with all major GIS and IOT systems. It is important to remember, that the key challenges are sustaining an integration technically, and building long term partnerships with data providers without the use of a costly in-house IT infrastructure and team.


Data concerning GPS devices, pre-departure testing, planning, pre-alerts, routings, geofences, and parking directories, contribute to location and risk Intelligence for a shipment. At the same time, this data sets base guidelines for a security monitoring process to trigger actionable alerts and notifications.


This information is typically produced by constant human collaboration between planning and security teams, utilizing multiple sources and systems to build this “launch code” to initiate a monitored shipment. We employ technology to empower customers and security teams by creating dedicated workflow automations and customised user environments which drastically reduce manual actions and consequently errors throughout the process.


As a result, all users are provided with up-to-date, accurate information, eliminating hundreds of various excel files across the ecosystem. We have delivered this with a lower failure than the SpaceX launch program, however the key challenge lies in understanding that all customers operate differently and a rigid workflow and UI will not solve this issue universally. The system must complement and adapt to customers’ workflow to deliver efficiencies and to add value. Where a TMS or ERP integration is available, “Launch Codes” can be automated by behind-the-scenes integration with ALL ONE VIEW.


Infographic showing how technology and humans collaborate. There are different stages described within the image: data, insights, inferences, analysis, action

Advancement of technology has assisted humans in defining automated algorithms and rules for a normal state, giving rise to exception monitoring. Exception monitoring is a catalyst for change and improvement, informing us of processes that are out of balance and identifying where energies need to be expended. Real-time tracking and monitoring is greatly enhanced by exception monitoring. The process of configuring exception rules is a prime example of collaboration between humans and technology.


For a security company, everything comes down to creation of efficient algorithms to generate actionable events, based on customer requirements. We can raise an event for a security operator to launch an intervention by using “Launch code”, time-variables, routings, geofences, motion and in-built sensors of a device. By combining our industry experience with the technology in ALL ONE VIEW, we can produce a wide array of alerts and notifications based on device sensors, time, traffic and environmental data for a shipment.

By applying customer tailored algorithms to customer UI only, we mitigate the risk of SOP cross-contamination and false alarms. This results in credible and actionable events created automatically for a security operator to intervene with full confidence. Thus, reducing the MTTD (Mean time to detect) and MTTC (Mean time to contain) for an incident.


“In God we trust, all others bring data.”- W. Edwards Deming.

The technology to produce predictive analytics and data insights is now easily available in the security industry. By simply throwing intelligent SQL queries into the data lake, data engineers and systems can produce detailed insights and predict trends, or future events in the supply chain.


Predictive analyses are AI-generated using historical and live data, for example, by using TensorFlow into ALL ONE VIEW, we train our data models. This assists in machine learning and enables deeper insights that produce actionable predictions and prescriptive recommendations.


The main challenge is to produce legible and informative data insights for non-technical users (i.e., planning and security teams in the ecosystem). Since human psychology varies from person to person, we do not always perceive data in the same way - we are triggered by colours, sounds, and in this case charts and graphs.


By empowering users to make their own choices, we create customized insights through a variety of charts and dashboards, rather than displaying the same visuals to everyone. That way, the data we present can inform and inspire those who are in the position to make a difference.


Infographic describing five types of analytics. From hindsight to foresight, there are five different stages that can be descrinbed by different questions: what happened, what is happening, why did it happen, what will happen and how can we make it happen.

Regrettably, the advancement of technology has also facilitated improper use of data by companies, governments, and criminals alike. This has created mistrust when it comes to privacy, transparency and cyber security.


For example, a delivery driver may not want to be tracked, or contacted. They might fear they are being spied on and their data is being collected, although they have not been assigned a high security and theft attractive shipment.


Privacy and transparency are some of our core values. Through technology, we ensure that that only the assigned driver on a given shipment is monitored, as per “Launch Code”. The system will simply not allow any tracking without auditable initiation from the system user. Once a shipment has been completed, the window of visibility for the shipment is closed for all users. This fosters an environment where users at all levels can benefit from the full support of monitoring, while performing a high value shipment.


To provide transparency across the board, we provide a live view of active shipments to all users. This enables all stakeholders to see how the security and delivery teams are performing in real-time. By complying with ISO and SOC standards, we ensure that we have concrete measures to mitigate and recover from cyber-attacks and disasters quickly.


“The greatest threat to our planet is the belief that someone else will save it.”– Robert Swan.

Manufacturing of telematics and related hardware is affected by microchip shortages, energy crises, economic warfare, political sanctions, and active wars. Technology has a trend of evolving faster and inventing efficient workarounds when faced with such obstacles. It is now more feasible than ever to make smart collaborations between data from existing hardware and diverse systems, without significant environmental impact, or financial investment. Data systems alone will not be enough to replace hardware completely in the near future, if data centres keep clocking more CO2 footprint, than the actual vehicles on the road. In fact, the servers in data centres dedicated to measuring CO2 footprint of shipments create significant environmental impact. Ideally, this measurement should be regulated and freely available over a public API. This would result in a reduction of hardware related emissions and at the same time provide credible and actionable data to improve sustainability.


“If it can’t be reduced, reused, repaired, rebuilt, refurbished, refinished, resold, recycled, or composted, then it should be restricted, designed or removed from production.” – Pete Seeger.

With ALL ONE VIEW, we strive to contribute to a security industry that creates sustainability and reduces e-waste.


Security companies assisted by technology and driven by their customer requirements are creating innovations to mitigate risk of theft. Technology can assist in automation, reduce manual effort and errors, however the focus needs to be on ensuring that the human operator remains the key decision maker, contextualizing analyses, and information in intelligent ways, that a machine cannot.


 

View this article in TAPA EMEA Vigilant Magazine