Over the years, terrorist attacks have been throwing challenging dimensions to the security of the globe and the nations. The quantum of the destruction of human lives, nature, public property is immense in the count. A serial four structure attacks in the US in September 2001 manifested the muscular reality of the terrorists. Almost a couple of decades passed by and this year, India witnessed the Pulwama attack on Feb 14th in which 40 CRPF personnel were martyred. It threw a sensation news to the globe and the entire nation obscured into the despair predicament with the high annoyance overflowing. These emotional articulations can never inflate the security of the common lives.
Waging a battle against the terrorist’s attack has been the prime requirement of the majority of the countries. Many countries and the Research Development Organizations are in indagation to prove the technology measures can mitigate the much happening losses. The heinous terrorist activities are getting rampant because of feeble examining activities and poor legislative laws. The disguise of the terrorist as a common citizen in public places is a huge challenge to be mitigated about. Huge suspicious components getting focused on public places easily without any investigation or detection. A densely populated territory becomes a hotspot for the terror zones.
Resorting to the advanced technology like Artificial Intelligence, Data Analytics which can be leveraged to combat these terrorist attacks. The data from the previous terrorist attacks can be processed to derive the insights and the integrated pattern analysis can be established. The designed pattern can detect suspicious objects or irrelevant activities happening in public places. The Artificial Intelligence being fed with the humongous data to analyze the attributes of the objects and the persons can detect the suspicious event that shall happen in a while. The infallible spots of any system/process/device/application can always eliminate the bottleneck for the malware or the suspicious activities to happen.
Key building elements in AI predictive analysis:
The AI algorithm for the predictive analysis to be spiked with the following:
- Prediction & Analysis
The prediction and the analysis of huge data using Machine Learning and the Predictive Framework can be integrated with the GIS system to identify the exact location of the suspicious attempts by embarking the border of each region. Temporal Probabilistic Algorithm framed by the University of Maryland has accumulated 770 key data elements from the past 20 years’ terrorist attacks. This helped in educating the AI system to determine the attack happening possibilities through the insights obtained from the frequency of attack happening, pattern and the other demographics and geographical information.
Machine Learning can read the audio and video of each frame, segment into the relevant bucket and notify the one which gets into the red bucket. The analytics as a part of Machine Learning can not only predict the attack, can also respond to the attacks on a real-time basis. The AI platform can immediately trigger an alarm or notify the concerned official to take action on exigency.
Flow depicting the AI Analytics in mitigating the terrorist attacks
- Machine Learning
- Advanced Analytics
- Predictive Analysis & Encryption Modules
- Temporal Probabilistic Algorithm
- Enterprise Database System
- PROLOG/LISP (AI Language – Specialized Software)
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- Data Computation (high clock speed processor, high RAM)
- Hard disk to store the logs and the data
- Input and Output Source device
- Node to drive the traffic to the core network
- Video Graphic Card (NVIDIA, Radeon)
- Surveillance System
- Monitoring Display System
- Wi-Fi/4G connectivity
- Video Analytics Software
- Operating System
- Video Management System (VMS)
A notch through Video Analytics
A simple solution of surveillance using the IP cameras with the video analytic features can save the lives of people and enrich the technology sustainability factor towards the terrorist attacks. The IP cameras deployed all over the critical places which are very much high to be terrorist prone can help the officer sitting in the central location to monitor the live feeds of the illegal activities recorded by the surveillance cameras.
1. Facial Recognition system can identify the whitelisted or blacklisted people by referring to the database of facial features of people stored in advance. It can enable the personnel to get into the restricted areas if he is whitelisted and generates an alarm in the monitoring station if the blacklisted person/terrorist enters that particular zone.
2. The same principle can be used in detecting the unidentified object, which is kept in a place unattended for a long duration. It can also detect suspicious objects and generate a token through an alarm. The monitoring officer can immediately allocate the concerned person to check out the object and once it is cleared, the same can be acknowledged.
3. Intelligent Transport Management System can trigger an alert on if a suspicious vehicle traveling in the opposite/wrong direction or the fake number plate of the vehicle been found.
4. Edge Analytics can process the raw data to the insightful information at each of the junction/edge nodes. The data need not be diverted to the central computation system and thus eliminating the huge thirst on the bandwidth.
Challenges through AI detection
The bottlenecks persist through Artificial Intelligence algorithms as well. The tool relies on the data fed to it from various sources and the higher degree of flaw in the data augmented will retard the output of the tool. Also, the AI’s response time to the new targeting approach of the terrorist is being one major limitation to be addressed at a higher pace.
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Original. Reposted with permission.