Quick Guide: Pitching Video Analytics to Your Boss
We're numb to them. Practically overrun with them. And chances are, you're sick of hearing about them.
You know exactly what I'm talking about.
Living in Silicon Valley, it's not uncommon to overhear happy hour conversations around blockchain, IoT, pitch strategies, or the classic explanation for most startups: It's like the Uber of [insert desired industry here]. Granted, the Valley is saturated with engineers, entrepreneurs, visionaries, and dreamers that arrived here with hopes of building the next unicorn.
For a true glimpse into life in the Bay Area, check out Overheard SF.
It's safe to say it, we're overrun with folks looking for and trying to sell the next best thing. This spawns the question: How do you successfully pitch useful tech to your boss or a client?
Whether you're pitching Cryptokitties or video analytics for security cameras, the formula is the same:
- State the problems. Be real, and be honest.
- Explain how you solve those problems.
- Make an awesome pitch deck.
In this article, I'll cover the first two steps. (Hint: Google is very good at answering the third)
The 6 major pain points of "dumb" cameras
Before we dive, a quick disclaimer. By dumb, I am merely referring to analog camera versus an IP camera.
1. You can't be in two places at once
Until Elon Musk releases a teleportation device (we'd even settle for a hyperloop), humans are still limited by transportation and the time and resources it demands.
Industries capitalize on this disadvantage. For example, cloud computing allows us to access documents and information from anywhere in the world, and thereby eliminating the need to travel to a specific location to access it.
In the same way that relying on USB thumb-drives to transport our documents is a thing of the past, so is depending on patrol officers for 100% of our surveillance. The cost that 24/7 surveillance demands vastly outweighs the benefits. Scheduling three, 24/7 patrol officers for round-the-clock costs nearly $600,000 annually. For most businesses, this is a big pill to swallow.
2. Making the dumb cameras talk to the smart ones
Security infrastructures have legacy systems in place. Just as iPhones have changed a lot in the past decade, so have surveillance systems.
How can you make legacy technology integrate with new investments?
This integration isn't always pretty. Device compatibility - or lack thereof - determines the destiny of an entire project. It can be next to impossible to manage all of these devices effectively.
3. Does the "D" in DVR stand for Difficult?
DVRs and NVRs can be hard to use. There's a black box element to its inner-workings. Teams struggle to pull historical data or video footage for police reports and evidence collection. In addition, it can be a challenge identifying if a camera is offline, which poses a security threat to the organization.
4. More money, more problems
Current solutions for video management is clunky and overpriced. Both Video Management Software (VMS) and Network Video Recorders (NVR) require hefty upfront investments. In today's world, tech advancements are rapid. Within 2-3 years, devices are outdated and ripe for replacement, but the large initial investment keeps companies locked into the same solution for years... even decades.
5. Upgrading your system = wasting your current hardware
For analog cameras, their purpose is passive surveillance. Passive surveillance is only useful if there is a security team watching all camera activity. As we discussed in pain point #1, staffing 24/7 patrollers and monitors is costly.
Traditionally, upgrading to an active surveillance system - one with intelligent video analytics that augments monotonous video monitoring - means ditching the old cameras and replacing them with newer IP cameras. This results in physical and financial waste.
6. Alert! Alert! Falling leaf detected!
In video analytics, there are 3 tiers of intelligence:
Level 1: Motion-based detection
Motion detection is the most popular form of analytics that a majority of cameras perform. It's an elementary form of detection, and results in a substantial amount of false positives. Home security cameras like Ring use motion detection to notify homeowners of activity in and around their property. If you use Ring or a similar tool, you might notice that the camera detects hundreds of activities each day: from moving trees or a car driving by to the neighbor's dog running through their backyard.
Level 2: Preliminary analytics
Mid-level video analytics is a step above motion detection, as it is able to recognize the shape or silhouette of a human. However, the computational power behind these analytics is limited. For instance, if a part of a person's body is out of the camera's view, it will not detect that person. Although it is more powerful than motion detection, there is still a high chance for false positives or undetected anomalies.
Level 3: A.I.-based analytics
Video analytics that are rooted in robust computer vision and machine learning algorithms result in minimal false positives and accurate detection of anomalies. In essence, computers are taught how to detect people, objects, and activities based on hundreds of hours' worth of video footage. As the software continues to run on cameras, it aggregates more data which makes the software more and more accurate. The only downside to these analytics: they demand substantial computing power. This is why most cameras can't run tier 3 analytics in real-time.
The 6 ways our automation tools can solve these issues
1. Keep it all in one place
Okay, we didn't invent the teleportation device (yet). But, we have something almost as cool: the Turing app and the Turing monitoring dashboard aggregate all video streams from cameras and IoT devices (like Nimbo). This gives you centralized visibility to all buildings and properties under your management.
Preview our new monitoring dashboard (it's awesome).
2. Everyone is speaking the same language
Turing lets your system be the melting pot that it is. Regardless of your cameras' brands, capabilities, and intelligence (or lack thereof), Turing syncs these devices to the same platform. In turn, you get a fluid, seamless experience managing your sites.
3. High-tech that's a piece of 🍰
Just because it's smart, doesn't mean it should be rocket science. The Turing app was designed like a consumer-facing product, which means it's a simple and friendly user interface. Filtering past video footage, exporting and sharing evidence, and scrolling through a timeline can be done with the tap of a button.
In addition, real-time camera statuses are shown reported, so if one goes offline unexpectedly, you're the first to know.
4. The beauty of the cloud
Businesses are becoming leaner and more agile than ever. Your security system must keep up. Our solution doesn't require any upfront hardware purchase. The software is cheap priced reasonably and easy to integrate with your system. Here's how it works:
- You decide to make your camera system smarter than ever (Woohoo, go you!).
- We connect your existing hardware (NVR/DVR and your cameras) to the AiVR box - which is the mini-computer that houses our video analytics software.
- You're ready to go with a monthly subscription and no upfront investment.
5. AiVR: the Redbull your camera deserves
No need to throw away your old cameras, AiVR will integrate with analog and IP cameras alike to deliver wicked smart video analytics. AiVR boxes give you wings™ open a new window for those old legacy cameras.
6. Adios undetected anomalies! Sayonara false positives!
A.I.-based video analytics is much more effective than motion-based detection and elementary-level analytics. No need to worry about trees moving in the wind or goofy pets anymore.
Posts by Tag
- Technology Trends
- Smart Security
- Artificial Intelligence
- Emerging Technology
- IoT devices
- Affordable Security
- Deep learning
- Machine learning
- Edge devices
- Small Business
- Edge computing
- Small Business Security
- Computer Vision
- Neural Networks
- ISC East
- Trade Show
- Video Analytics