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Navigating the Future Discover How Edge AI is Revolutionizing Autonomous Vehicles

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Autonomous vehicles

This article marks the beginning of an insightful blog series dedicated to exploring the transformative impact of Edge AI on various sectors, starting with autonomous vehicles. Over the coming weeks, we will delve into the nuances of Edge AI, its technical foundations, and how it’s reshaping industries such as autonomous vehicles, consumer electronics, IoT devices, and smart sensors. Stay tuned as we unpack this cutting-edge technology’s advancements, challenges, and future prospects.

Imagine a world where cars drive themselves, adapting instantly to their surroundings with minimal latency. This isn’t science fiction; it’s the promise of Edge AI autonomous vehicles. Edge AI combines artificial intelligence and edge computing to process data locally, right where it’s generated, instead of relying on centralized cloud servers. In this blog, we’ll explore Edge AI’s profound impact on autonomous vehicles, offering insights into its advantages, challenges, and future potential. Whether you’re a CTO, CMO, tech enthusiast, CEO, or business owner, understanding this technology’s implications can help you stay ahead of the curve.

Understanding Edge AI

Edge AI refers to the deployment of AI algorithms on devices close to the source of data generation, such as sensors in autonomous vehicles. This approach reduces the need for constant communication with distant servers, resulting in faster decision-making and lower latency. By processing data at the edge, these vehicles can make real-time decisions essential for safe and efficient operation. Edge AI-powered vehicles can also communicate with other vehicles, road infrastructure, and pedestrians, enhancing their situational awareness and overall performance.

The integration of Edge AI into autonomous vehicles brings several notable benefits. Primarily, the ability to process data locally enhances the vehicle’s speed and responsiveness, which is crucial in dynamic driving environments. This reduces the lag time associated with sending data to and from cloud servers, ensuring that autonomous vehicles can react instantaneously to sudden changes such as a pedestrian stepping into the road or an unexpected obstacle appearing. Additionally, decentralized data processing helps to maintain a higher level of privacy and security, as sensitive information does not need to be transmitted over potentially vulnerable networks.

Google’s Waymo Self Driving Cars

As of June 2024, seven hundred Waymo self driving cars are on public roadways.

In this captivating video, we explore how Google’s Waymo self-driving cars are making waves in San Francisco and Los Angeles, showcasing the transformative power of autonomous technology in urban environments. Watch as these vehicles navigate bustling streets, interact seamlessly with traffic, and adapt to various driving conditions, all while prioritizing safety. With real-time data processing powered by Edge AI, these cars demonstrate unprecedented efficiency and reliability, paving the way for the future of transportation. Join us on this journey to witness the evolution of mobility and the potential for self-driving cars to reshape our cities.

Enhancing Real-Time Decision Making

Decision Making

Edge AI plays a crucial role in advancing the safety, efficiency, and robustness of autonomous driving technology. It enhances real-time decision-making by processing data on the vehicle itself, thereby reducing delays associated with traditional cloud-based systems. For instance, an autonomous car can analyze and respond almost instantaneously to unexpected obstacles, improving safety and performance, especially in challenging driving conditions like heavy traffic or adverse weather.

Additionally, Edge AI fosters a more reliable autonomous driving experience through redundancy and fault tolerance. By enabling multiple AI processes to occur independently at the edge, vehicles can maintain functionality even if one process fails. This approach also reduces bandwidth usage, mitigating the risks of network congestion and data bottlenecks. Collectively, these advantages illustrate the instrumental role of Edge AI in the future of autonomous driving.

Improving Safety and Reliability

Safety is paramount in autonomous driving, and Edge AI plays a crucial role in enhancing it. With the ability to process data locally, vehicles can detect and react to hazards more quickly. Think of a pedestrian suddenly stepping onto the road. Edge AI allows the vehicle to recognize the danger and take immediate action, potentially preventing accidents. This localized processing also adds a layer of reliability, as the vehicle remains operational even if network connectivity is lost. In contrast, cloud-based systems may experience downtime if connection issues arise.

Beyond immediate hazard detection, Edge AI contributes to more nuanced safety measures through continuous environment monitoring and adaptive learning. This means the vehicle can learn from its surroundings, improving its response to repeated patterns of certain conditions like heavy pedestrian traffic near schools or sharp turns in mountainous roads. Edge AI systems can be continually updated with new data and software enhancements without needing extensive downtime, ensuring the vehicles are up-to-date with the latest safety algorithms and threat detection models.

Lastly, Edge AI facilitates better fleet management for companies that operate multiple autonomous vehicles. By collecting and processing data locally, fleet operators can monitor vehicle performance and health in real-time, scheduling proactive maintenance and detecting potential issues before they lead to breakdowns or safety incidents. This degree of oversight ensures that each vehicle remains in optimal working condition, enhancing the overall safety and reliability of autonomous transportation systems.

Reducing Operational Costs

Operational Costs

Edge AI can significantly reduce operational costs for autonomous vehicle fleets. By minimizing data transmission to cloud servers, companies can save on bandwidth and storage expenses. Additionally, local processing reduces the reliance on expensive, high-speed internet connections. Over time, these cost savings can be substantial, making autonomous vehicles more economically viable for businesses. This can accelerate the adoption of autonomous vehicles, leading to increased efficiency and productivity in transportation.

Enhancing User Experience

User Experience

For passengers, the user experience is a critical aspect of autonomous travel. Edge AI contributes to a smoother and more responsive ride. Imagine a scenario where the vehicle needs to reroute due to sudden traffic congestion. Edge AI enables quick recalculations and adjustments, ensuring passengers reach their destinations efficiently. This improved responsiveness can lead to higher satisfaction and increased adoption of autonomous vehicles.

Pros and Cons of Edge AI Autonomous Vehicles

Pros

One of the most significant advantages of Edge AI is low latency. Immediate data processing allows vehicles to make real-time decisions, thereby enhancing safety and performance. The quicker a vehicle can respond to its environment, the safer and more efficient it becomes.

Another considerable benefit is reliability. With continuous operation even without network connectivity, Edge AI ensures that the vehicle can always make critical decisions. This resilience is especially important in areas with poor network coverage or temporary signal loss.

Cost savings present another advantage. By reducing the need to constantly transmit data to and from cloud servers, operational expenses connected to bandwidth and storage are minimized. This cost efficiency makes autonomous vehicle fleets more economically viable, encouraging broader adoption.

Cons

Despite its advantages, Edge AI does come with hardware limitations. Edge devices often have constraints in terms of processing power and storage capacity. This limitation can affect the vehicles’ ability to process complex algorithms locally, posing a challenge that needs to be overcome with advanced technology and engineering.
Complexity is another challenge. Integrating Edge AI into autonomous systems requires sophisticated algorithms and robust infrastructure. The intricacies involved in ensuring seamless operation can be a hurdle for vehicle manufacturers looking to adopt this technology.

Finally, security risks are a significant concern. Localized data processing means that Edge AI systems can be more vulnerable to physical tampering and cyber threats. Securing the data and ensuring the integrity of the processing units are critical tasks that must be addressed to maintain the safety and reliability of autonomous vehicles. Understanding these pros and cons is essential for businesses and technologists aiming to harness the full potential of Edge AI in autonomous vehicles.

Future of Edge AI in Autonomous Vehicles

Future

The future of Edge AI in autonomous vehicles looks promising. With advancements in AI algorithms and edge computing hardware, we can expect even greater capabilities and efficiencies. Upcoming developments may include more sophisticated object detection, predictive maintenance, and enhanced passenger personalization. These innovations will continue to push the boundaries of what autonomous vehicles can achieve. As technology improves, it is vital to address the associated challenges and risks to ensure the safe and seamless integration of Edge AI in autonomous vehicles.

The journey towards fully autonomous vehicles continues, with Edge AI playing a significant role in shaping its future. Therefore, businesses, researchers, and policymakers must collaborate and invest in this innovative technology to bring us closer to a safer and more efficient transportation system. The potential benefits are vast, and with continued development and refinement, we can expect even greater advancements in the near future. Embracing Edge AI in autonomous vehicles will undoubtedly pave the way towards a smarter and more connected future. Let’s continue to explore the possibilities and strive towards a world where vehicles can navigate the roads with precision, speed, and safety through the power of Edge AI.

Conclusion

Edge AI is set to revolutionize autonomous vehicles, offering significant improvements in safety, efficiency, and user experience. By harnessing the power of local data processing, these vehicles can make real-time decisions, ensuring smoother and safer rides. Enhanced reliability, even in areas with poor network connectivity, further solidifies Edge AI’s role in the future of transportation. Additionally, the operational cost savings associated with minimized data transmission can lead to a more economically viable approach for businesses, accelerating the adoption of autonomous vehicles.

Understanding the full impact and potential of Edge AI is crucial for business leaders and technologists. Anticipating these changes allows for better strategic planning and investment in infrastructure that supports this advanced technology. As we continue to explore the possibilities of Edge AI, it’s essential to address the challenges related to hardware limitations, complexity, and security risks to fully leverage its benefits.

Stay tuned for our next blog in the series where we’ll delve into Edge AI in Consumer Electronics. We’ll explore how this technology is transforming everyday devices, from smart home systems to personal gadgets, enhancing daily life through improved functionality, responsiveness, and user experience. The journey of Edge AI is just beginning, and its influence is expected to permeate various sectors, bringing unprecedented advancements and efficiencies. Embracing this innovation will undoubtedly pave the way towards a smarter, safer, and more interconnected world.

How Zigbee Pro Makes Life Easier for IoT Developers

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The IoT has proliferated our everyday lives in a growing variety of ways. In 2021, there were more than 10 billion active IoT devices. That number is expected to grow past 25.4 billion by 2030. IoT solutions will generate $4-11 trillion in economic value by 2025.

Hundreds of manufacturers create IoT devices of all varieties—interoperability is necessity. In order to facilitate this, IoT developers generally adhere to a communications protocol known as Zigbee Pro.

WHAT IS ZIGBEE PRO?

 

Zigbee Pro is a low power, low data rate Wireless Personal Area Network (WPAN) protocol which streamlines device connections. The goal of the protocol is to deliver a single communications standard that simplifies the nauseating array of proprietary APIs and wireless technologies used by IoT manufacturers.

Zigbee Pro is the latest in a line of protocols. The certification process is facilitated by the Zigbee Alliance—now commonly known as the Connectivity Standards Alliance—which formed in 2002. The Connectivity Standards developed the first version of Zigbee in 2004 and gradually rolled out improved versions until the most current version in 2014.

HOW DOES IT WORK?

Zigbee is composed of a number of layers that form a protocol stack. Each layer contributes functionality to the ones below it, making it easier for developers to deploy these functions without explicitly having to write them. The layers include a radio communication layer based on the IEEE standard 802.15.4, a network layer (Zigbee Pro), the application layer known as Dotdot, and the certification layer which is compliant with the Connectivity Standards Alliance.

One of the focuses of the Zigbee standard is to deliver low-power requirements. Battery powered devices must have a 2 year battery life in order to be certified.

ZIGBEE DEVICES

Mesh networking enables Zigbee networks to operate more consistently than WiFi and Bluetooth. Each device on the network becomes a repeater, which ensures that losing one device won’t affect the other devices in the mesh.

There are three classes of Zigbee devices:

Zigbee Coordinator – The coordinator forms the root of the network tree, storing information about the network and functioning as a repository for security keys. This is generally the hub, bridge, or smart home controller—such as the app from which you control your smart home.

Zigbee Router – The router can run application functions as well as act as an intermediate router to pass data on to other devices. The router is generally a typical IoT device, such as a powered lightbulb.

Zigbee End Device – This is the simplest type of device—requiring the least power and memory to perform the most basic functions. It cannot relay data and its simplicity enables it to be asleep the majority of the time. An example of an end device would be a smart switch or a sensor that only sends a notification when a specific event occurs.

The Zigbee Pro protocol has become the gold standard for IoT developers. Many commercial IoT apps and smart home controllers function under the Zigbee Pro protocol. Examples include: Samsung SmartThings Hub, Amazon Echo, and the Philips Hue Bridge.

How Apple & Google Are Enhancing Battery Life and What We as App Developers Can Do to Help

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In 1799, Italian physicist Alessandro Volta created the first electrical battery, disproving the theory that electricity could only be created by human beings. Fast forward 250 years, brands like Duracell and Energizer popularized alkaline batteries—which are effective, inexpensive and soon become the key to powering household devices. In 1991, Sony released the first commercial rechargeable lithium-ion battery. Although lithium-ion batteries have come a long way since the 90s, to this day they power most smartphones and many other modern devices.

While batteries have come a long way, so have the capabilities of the devices which need them. For consumers, battery life is one of the most important features when purchasing hardware. Applications which drain a device’s battery are less likely to retain their users. Software developers are wise to understand the latest trends in battery optimization in order to build more efficient and user-friendly applications.

HARDWARE

Lithium-ion batteries remain the most prevalent battery technology, but a new technology lies on the horizon. Graphene batteries are similar to traditional batteries, however, the composition of one or both electrodes differ. Graphene batteries increase electrode density and lead to faster cycle times as well as the ability to improve a battery’s lifespan. Samsung is allegedly developing a smartphone powered by a graphene battery that could fully charge its device within 30 minutes. Although the technology is thinner, lighter, and more efficient, production of pure graphene batteries can be incredibly expensive, which may inhibit its proliferation in the short-term.

Hardware companies are also coming up with less technologically innovative solutions to improve battery life. Many companies are simply attempting to cram larger batteries into devices. A more elegant solution is the inclusion of multiple batteries. The OnePlus 9 has a dual cell battery. Employing multiple smaller batteries means both batteries charge faster than a single cell battery.

SOFTWARE

Apple and Google are eager to please their end-users by employing techniques to help optimize battery life. In addition, they take care to keep app developers updated with the latest techniques via their respective developer sites.

Android 11 includes a feature that allows users to freeze apps when they are cached to prevent their execution. Android 10 introduced a “SystemHealthManager” that resets battery usage statistics whenever the device is unplugged, after a device is fully charged or goes from being mostly empty to mostly charged—what the OS considers a “Major charging event”.

Apple has a better track record of consuming less battery than Android. iOS 13 and later introduced Optimized Battery Charging, enabling iPhones to learn from your daily charging routine to improve battery lifespan. The new feature prevents iPhones from charging up to 100% to reduce the amount of time the battery remains fully charged. On-site machine learning then ensures that your battery is fully charged by the time the user wakes up based on their daily routines.

Apple also offers a comprehensive graph for users to understand how much battery is being used by which apps, off screen and on screen, under the Battery tab of each devices Settings.

WHAT APPLICATION DEVELOPERS CAN DO

App developers see a 73% churn rate within the first 90 days of downloading an app, leaving very little room for errors or negative factors like battery drainage. There are a number of techniques application developers can employ in their design to reduce and optimize battery-intensive processes.

It’s vital to review each respective app store’s battery saving standards. Both Android and Apple offer a variety of simple yet vital tips for reducing battery drain—such as limiting the frequency that an app asks for a device’s location and inter-app broadcasting.

One of the most important tips is to reduce the frequency of network refreshes. Identify redundant operations and cut them out. For instance, can downloaded data be cached rather than using the radio repeatedly to re-download it? Are there tasks that can be deferred by the app until the device is charging? Backing up data to the cloud can consume a lot of battery on a task that is not always time sensitive.

Wake locks keep the phone’s screen on when using an app. There was a time where wake locks were frequently employed—but now it is frowned upon. Use wake locks only when absolutely necessary—if at all.

CONCLUSION

Software developers need to be attentive to battery drain throughout the process of building their application. This begins at conception, through programming, all the way into a robust testing process to identify potential battery drainage pitfalls. Attention to the details of battery optimization will lead to better, more user-friendly applications.

Learn How Google Bests ARKit with Android’s ARCore

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Previously, we covered the strengths of ARKit 4 in our blog Learn How Apple Tightened Their Grip on the AR Market with the Release of ARKit 4. This week, we will explore all that Android’s ARCore has to offer.

All signs point toward continued growth in the Augmented Reality space. As the latest generations of devices are equipped with enhanced hardware and camera features, applications employing AR have seen increasing adoption. While ARCore represents a breakthrough for the Android platform, it is not Google’s first endeavor into building an AR platform.

HISTORY OF GOOGLE AR

In summer 2014, Google launched their first AR platform Project Tango.

Project Tango received consistent updates, but never achieved mass adoption. Tango’s functionality was limited to three devices which could run it, including the Lenovo Phab 2 Pro which ultimately suffered from numerous issues. While it was ahead of its time, it didn’t receive the level of hype ARKit did. In March 2018, Google announced that it will no longer support Project Tango and that the tech titan will be continuing AR Development with ARCore.

ARCORE

ARCore uses three main technologies to integrate virtual content with the world through the camera:

  • Motion tracking
  • Environmental understanding
  • Light estimation

It tracks the position of the device as it moves and gradually builds its own understanding of the real world. As of now, ARCore is available for development on the following devices:

ARCORE VS. ARKIT

ARCore and ARKit have quite a bit in common. They are both compatible with Unity. They both feature a similar level of capability for sensing changes in lighting and accessing motion sensors. When it comes to mapping, ARCore is ahead of ARKit. ARCore has access to a larger dataset which boosts both the speed and quality of mapping achieved through the collection of 3D environmental information. ARKit cannot store as much local condition data and information. ARCore can also support cross-platform development—meaning you can build ARCore applications for iOS devices, while ARKit is exclusively compatible with iOS devices.

The main cons of ARCore in relation to ARKit mainly have to do with their adoption. In 2019, ARKit was on 650 million devices while there were only 400 million ARCore-enabled devices. ARKit yields 4,000+ results on GitHub while ARCore only contains 1,400+. Ultimately, iOS devices are superior to software-driven Android devices—particularly given the TrueDepth Camera—meaning that AR applications will run better on iOS devices regardless of what platform they are on.

OVERALL

It is safe to say that ARCore is the more robust platform for AR development; however, ARKit is the most popular and most widely usable AR platform. We recommend spending time determining the exact level of usability you need, as well as the demographics of your target audience.

For supplementary reading, check out this great rundown of the best ARCore apps of 2021 from Tom’s Guide.

The Real Power of Artificial Intelligence

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Technological innovations expand the possibilities of our world, but they can also shake-up society in a disorienting manner. Periods of major technological advancement are often marked by alienation. While our generation has seen the boon of the Internet, the path to a new world may be paved with Artificial Intelligence.

WHAT IS ARTIFICIAL INTELLIGENCE

Artificial intelligence is defined as the development of computer systems to perform tasks that normally require human intelligence, including speech recognition, visual perception, and decision-making. As recently as a decade ago, artificial intelligence evoked the image of robots, but AI is software not hardware. For app developers, the modern-day realization of artificial intelligence takes on a more amorphous form. AI is on all of your favorite platforms, matching the names and faces of your friends. It’s planning the playlist when you hit shuffle on Apple Music. It’s curating the best Twitter content from you based on data-driven logic that is often too complex even for the humans who programmed the AI to decipher.

MACHINE LEARNING

Currently, Machine Learning is the primary means of achieving artificial intelligence. Machine Learning is the ability for a machine to continuously improve its performance without humans having to explain exactly how to accomplish all of the tasks it has been given. Web and Software programmers create algorithms capable of recognizing patterns in data imperceptible to the human eye and alter their behavior based on them.

For example, Google’s autonomous cars view the road through a camera that streams the footage to a database that centralizes the information of all cars. In other words, when one car learns something—like an image or a flaw in the system—then all the cars learn it.

For the past 50 years, computer programming has focused on codifying existing knowledge and procedures and embedding them in machines. Now, computers can learn from examples to generate knowledge. Thus, Artificial Intelligence has already permanently disrupted the standard flow of knowledge from human to computer and vice versa.

PERCEPTION AND COGNITION

Machine learning has enabled the two biggest advances in artificial intelligence:  perception and cognition. Perception is the ability to sense, while cognition is the ability to reason. In a machine’s case, perception refers to the ability to detect objects without being explicitly told and cognition refers to the ability to identify patterns to form new knowledge.

Perception allows machines to understand aspects of the world in which they are situated and lays the groundwork for their ability to interact with the world. Advancements in voice recognition have been some of the most useful. In 2007, despite its incredibly limited functionality, Siri was an anomaly that immediately generated comparisons to HAL, the Artificial Intelligence in 2001: A Space Odyssey. 10 years later, the fact that iOS 11 enables Siri to translate French, German, Italian, Mandarin and Spanish is a passing story in our media lifecycle.

Image recognition has also advanced dramatically. Facebook and iOS both can recognize your friends’ faces and help you tag them appropriately. Vision systems (like the ones used in autonomous cars) formerly made a mistake when identifying a pedestrian once in every 30 frames. Today, the same systems err less than once in 30 million frames.

EXPANSION

AI has already made become a staple of mainstream technology products. Across every industry, decision-making executives are looking to capitalize on what AI can do for their business. No doubt whoever answers those questions first will have a major edge on their competitors.

Next week, we will explore the impact of AI on the Digital Marketing industry in the next installment of our blog series on AI.

Securing Your IoT Devices Must Become a Top Priority

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The Internet of Things has seen unprecedented growth the past few years. With an explosion of commercial products arriving on the marketplace, the Internet of Things has entered the public lexicon. However,  companies rushing to provide IoT devices to consumers often cut corners with regard to security, causing major IoT security issues nationwide.

In 2015, hackers proved to Wired they could remotely hack a smartcar on the highway, kill the engine and control key functions. Dick Cheney’s cardiologist disabled WiFi capabilities on his pacemaker, fearing an attack by a hacker.  Most recently, the October 21st cyber attack on Dyn brought internet browsing to a halt for hours while Dyn struggled to restore service.

Although the attack on Dyn seems to be independent of a nation-state, it has caused a ruckus in the tech community. A millions-strong army of IoT devices, including webcams and DVRs, were conscripted with a botnet which launched the historically large denial-of-service attack. Little effort has been made to make common consumers aware of the security threats posed by IoT devices. A toy Barbie can become the back door to the home network, providing access to PCs, televisions, refrigerators and more. Given the disturbing frequency of hacks in the past year, IoT security has come to the forefront of top concerns for IoT developers.

SECURING CURRENT DEVICES

The amount of insecure devices already in the market complicates the Internet of Things security problem. IoT hacks will continue to happen until the industry can shrink vulnerable devices. Securing current devices is a top priority for app developers. Apple has made an effort to combat this problem by creating very rigorous security requirements for HomeKit compatible apps.

The European Union is currently considering laws to force compliance with security standards. The plan would be for secure devices to have a label which ensures consumers the internet-connected device complies with security standards. The current EU labeling system which rates devices based on energy consumption could prove an effective template for this new cybersecurity rating system.

ISPs COULD BE THE KEY

Internet service providers could be a major part of the solution when it comes to IoT Security. Providers can block or filter malicious traffic driven by malware through recognizing patterns. Many ISPs use BCP38, a standard which reduces the process hackers use to transmit network packets with fake sender addresses.

ISPs can also notify customers, both corporate and individuals, if they find a device on their network sending or receiving malicious traffic. ISPs already comply with the Digital Millennium Copyright Act which requires internet providers to warn customers if they detect possible illegal file sharing.

With the smarthome and over 1.9 billion devices predicted to be shipped in 2019, IoT security has never been a more important issue. Cyber attacks within the US frequently claim the front page of the mainstream media. CIO describes the Dyn attacks as a wake-up call for retailers. The combination of a mass adoption of IoT and an environment fraught with security concerns means there will be big money in IoT security R & D and a potential slow-down in time-to-market pipeline for IoT products.

Will the federal government get involved in instituting security regulations on IoT devices, or will it be up to tech companies and consumers to demand security? Whatever the outcome, this past year has proved IoT security should be a major concern for developers.

Mind Over Matter: Why Apple Downsized with the iPhone SE

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On March 21st, Apple announced a smaller 9.7 inch iPad Pro model, a price drop for Apple Watch and new nylon bands, and most importantly, their latest smartphone: the iPhone SE. While the iPhone 6 and 6+ represented the largest phones in Apple history, Apple elected to go smaller with their latest release. The iPhone SE is the size of an iPhone 5 with the processor of an iPhone 6, essentially recycling the aesthetic design of the iPhone with the speed of an iPhone 6.

When it comes to smartphones, screen size matters. Statistics show over half of YouTube views come from mobile devices and the average YouTube session lasts for over 40 minutes. Although people are watching more video than ever on their phones, it doesn’t mean bigger is always better. Many scorned the iPhone 6+ for being too large and clunky. The iPhone SE represents a more affordable option with all the processing power of an iPhone 6 on a smaller screen.

iPhone SE vs. iPhone 6s (via 9 to 5 Mac)

When it comes to specs, the iPhone SE is no slouch. The iPhone SE screen measures at 4.87 x 2.31 x .30 inches, the exact same dimensions as the iPhone 5. Like the iPhone 6, the iPhone SE has retina display. The phone has an A8 chip with 64-bit architecture and an M8 motion coprocessor, like the iPhone 6. While the iPhone 6 has 1334 x 750 pixels (326 PPI), iPhone SE has slightly fewer with 1136 x 640 pixels. The SE’s rear camera is identical to the iPhone 6. The one area in which the SE exceeds the iPhone 6 is in battery life: iPhone SE has 1642 mAh while iPhone 6S has 1715. The SE’s smaller, lower-resolution display ensures users will receive 20% longer 3G internet surfing time on the SE, 30% more 4G, and 20% longer when watching video.

Check out this awesome video review of the iPhone SE by The Verge:

Apple is expected to announce the iPhone 7 in 2017. Techies expect the iPhone 7 to be a major advancement in the Apple lineage. With a large announcement looming, the iPhone SE is designed to diversify their product line with a cost-friendly option to hold Apple lovers over and combat the probability that iPhone sales will decline for the first time in company history in 2016.

At $399 without a contract, Apple seems to be aiming to take a bite out of the cost-friendly Android market. Although the average price for an Android smartphone was about $215 at the end of 2015, the difference may entice those drawn by the allure of Apple products.

Last year, Apple took a big bite out of China. In the 4th Quarter of 2015, iPhone sales grew 33% in China. Having recently lost their crown as largest smartphone vendor in China to Xiaomi, the Chinese market represents a major area of potential growth for Apple. Affordable options with premium processing power have the potential to eat into Android’s sales in rural and urban Chinese markets.

The move to more affordable iPhones began with the iPhone 5c; however, supply chain problems taught Apple that using new material can produce unforeseen difficulties. Foxconn announced that the iPhone 5 was the most difficult device they have ever assembled. By recycling iPhone 5 design, materials, and supply chain, iPhone SE is a much cheaper product to create and manufacture.

Some argue that smartphone UX has not advanced with screen-size and few phones have UX features specifically designed for large-screen devices. Whether or not this influenced Apple’s decision to downsize, the affordability, overseas sales potential, and diversified design certainly make the iPhone SE an attractive device for the company. The question now becomes: will Apple unveil a larger iPhone 7 in 2017 with groundbreaking large-screen UX? We’ll have to wait and see.

Safety First: Mobile Security Is More Than Worth the Investment

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Having established the top mobile app trends for 2016 with our blog App to the Future, the Mystic Media blog is currently exploring each of the top trends in greater detail with a five-part series. This week, in Part 3 of our Top Mobile App Development Trends series, we will be examining security.

2015 saw several major data breaches, including 87 million patient records from Anthem and 21.5 million security clearance apps from the U.S. Office of Personnel Management. The European Union is currently crafting a General Data Protection Regulation designed to strengthen and unify data protection.

Gartner correctly predicted that over 75% of mobile applications would fail basic security tests in 2015. Many mobile companies are sacrificing security to attain quicker turn-around on smaller budgets, and the result has been disastrous for many. Even Apple hasn’t been safe from mobile app hacks.

Mobile application security is an integral part of the app development process worthy of the same level of attention as app creators give to design, marketing and functionality. With that in mind, here are some of the top app security trends for 2016:

DevOps Protocol on the Rise

In a recent RackSpace Survey of 700 IT manager and business leaders, 66% of respondents had implemented DevOps practices and 79% of those who had yet to implement DevOps planned to by the end of 2015.

DevOps is an approach to app development that emphasizes collaboration between software development, IT operations, security and quality assurance through all stages of the app development process under one automated umbrella. Utilizing a DevOps protocol improves app security by bringing the IT security team in at an early stage to guide the development process away from potential security threats. App Developers gravitate toward DevOps since it speeds up the time to market while increasing innovation. Like a conveyer belt, DevOps puts a system of checks and balances in place at all stages to ensure that the product will be sufficient for delivery.

By opening up the app development process, security team members can inject security into the code early in the development process and eliminate vulnerabilities before they become threats.

Security Risks In Wearable Tech

Wearable technology is on the rise not only in the marketplace, but as a major security vulnerability for businesses. With the technology in nascent stages, developers have been more concerned with creating a functional strategy for the wearable platform than they have been with improving security. Health and Fitness apps leave users the most vulnerable by constantly monitoring the user’s heartbeat, movement and location. With limited UI and an emphasis on usability, wearables severely lack in security features. App developers looking to create safe apps for this platform will have to innovate and dictate the trends in order to create apps that don’t put the user at risk.

IoT (Internet of Things) & BYOD (Bring-Your-Own-Device)

With the workplace increasingly becoming virtual, malicious hackers acting through the Internet of Things are targeting personal mobile devices in order to find vulnerabilities in businesses.

Bring-Your-Own-Device (BYOD) has increased in popularity in work cultures, each of which represents a potential vulnerability . Smartphone owners generally don’t invest in security on their personal devices with the same thoroughness as a business would when issuing work devices. Due to the boon of mobile work apps, many app developers are cutting corners to meet demand by sacrificing security in service of quicker turnover.

Wise and experienced app developers know you can’t put a price on safety, and they take the necessary precautions to protect the integrity of the app for its users and the app owner.

Major organizations must understand IoT and how it can improve or threaten their business through their employees’ mobile devices. By encouraging a culture of collaboration and welcoming unique expertise into the app development process at an early stage, DevOps practices help ingrain necessary knowledge about IoT and mobile security into organizations.

That’s it for app security! Be on the lookout for part 4 of our series on the top mobile app development trends for 2016 next week when we explore the Internet of Things.

Rise to the Top of Google SEO with Responsive Design

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When designing a website, web developers have both practical and aesthetic concerns. From a practical standpoint, a website must reach and connect with its core audience. Due to the rise of mobile technology, it’s important for a site to have mobile functionality so that it can reach the multitudes surfing the web on their mobile devices. The most efficient, cost-effective & effective way is to develop a responsive website. Responsive design not only helps reach a mobile audience, it also increases overall SEO so that the website will rank higher in search engines.

For those unfamiliar with responsive design, check out this quick 60-second review:

When it comes to SEO, Google is king. As of October 2015, studies show the massive tech titan owns about 63.9% of the search engine market share. In February 2015, Google announced they will be emphasizing mobile-friendly search results. In their own words: “Starting April 21, we will be expanding our use of mobile-friendliness as a ranking signal.”

In accordance with their announcement, Google Adwords charges less for a keyword when the landing page is optimized for mobile. Responsive websites represent a major incentive for advertising on Google since responsive design guarantees presentation will accommodate the device regardless of whether it’s a mobile device or a computer.

Responsively designed sites offer a common landing page for all devices, consolidating the amount of links and improving the SEO. If a desktop or laptop user iMessages the link to an iPhone, they can click on it and immediately prompt the same web page rather than a different page optimized for mobile. Instead of duplicating content with separate sites for mobile and desktop mediums, responsive design ensures brand and information continuity with a singular master site.

According to Sociomantic, over half of online shoppers use more than one device. A responsive website not only ensures a consistent UI and brand experience, it eliminates maintenance cost by reducing the amount of websites one is required to maintain. The better a site is, the lower the bounce rate is, and the higher it will rank in Google. For businesses looking to succeed, responsive is almost always the best form of web design.

Mystic Media is a web design and application development company based in Salt Lake City, Utah and specializes in responsive design. For more information, click here or contact us by phone at 801.994.6815.

Best Sleep Apps: Get Better Rest Using your iPhone

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25% of people in the US report trouble with sleep. Sleep deprivation can cause decreased performance and alertness, impaired memory, stress, depression and more. Luckily, we live in a golden age of technology. App developers are actively working to develop iOS and Android apps which will help you get better sleep using your iPhone or Android smartphone. Below find some of the best iOS & Android sleep apps on the market.

BEDDIT

Beddit has made a name for itself as one of the consensus top sleep apps on iOS and Android. Beddit measures cardiorespiratory functions by detecting movements caused by respiration and heartbeats. The app uses an ultra-thin film sensor which goes under your sheet in order to  measure sleep time, sleep latency, awakenings, resting heart rate and snoring. While the Beddit app is free, the sleep monitor ranges from $99.99 – $149.99.

Beddit is available for iOS (iPhone and Apple Watch) via iTunes, as well as Android devices via Google Play.

SLEEP CYCLE

For those looking for a more cost-friendly sleep app, Sleep Cycle is another of the top Android and iOS sleep apps—and it’s only $0.99. Developed by Northcube, Sleep Cycle uses the iPhone’s accelerometer to track sleep phases. When we sleep, we go through multiple states in our sleep cycle, the deepest of which is REM sleep where dreams occur. Sleep Cycle monitors movements using sound analysis and wakes users up during light sleep to ensure users feel naturally rested.

Sleep Cycle is currently available for Android and iOS for free with in-app purchases.

SLEEP GENIUS

If you’re searching for the most high-tech sleep app, look no further than Sleep Genius. Designed with the help of research by NASA, Sleep Genius helps you determine the perfect bedtime, revives you with a soothing alarm, and even helps you make the most of your naps with psychoacoustic music scientifically designed to trigger a relaxation response. NASA’s magazine, SPINOFF, recently celebrated the app for its use of NASA technology to create a better world.

At $4.99, the app is moderately priced in iTunes and Google Play. It’s a steal considering the level of high tech utilized to make it work.

Looking for more great sleep apps? Check out these awesome curated lists from HealthLine and Tom’s Guide.

Mystic Media is an Android & iOS app development, web design and strategic marketing firm located in Salt Lake City, Utah. Contact us today by clicking here or by phone at 801.994.6815