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How Integrated GPS Works With Smart EV Routing



CManigandan Chokkalinkam Hacker Noon profile picture

@cmanigandanCManigandan Chokkalinkam

Founder / Accelerating startups with innovative IoT and embedded solutions @ Radinno Labs

Going by the number of countries that Tesla has got its footprints, it’s beyond doubt that the electrification of vehicles is on a tremendous rise. Passenger EV sales have seen a staggering five-fold increase in the last five years and we’re witnessing a movement that is growing slowly but steadily.

As Li-ion battery pack prices dropped by 87% in the past decade and policymakers are making the move for building better charging infrastructure, the EV share of total vehicle sales is projected to hit 58% by 2040.

Agreed that the future looks green and promising with reduced CO2 emissions and lower running costs of EVs prompting more people to consider owning EVs. But the sparse charging infrastructure and comparatively limited range of economical pure electric vehicles instill the gnawing sense of range anxiety (Yes, it’s an actual thing!) in potential buyers.

Until the number of charging stations catch up with those of fuel pumps, relying on optimal charging through EV routing schemes brings down anxiety levels. Apple launched an EV routing feature to eliminate range anxiety and is working with the likes of BMW to ease routing in its range of electric vehicles.

Warning! Strange EV terms ahead

Before we dive in and talk more about EV routing and how inbuilt GPS in EVs would put drivers’ fears at bay, let’s take a quick look at a few EV – specific terms we’ll be using in this article.

Range – The EV equivalent to the mileage of a petrol or diesel-powered vehicle; the range is the maximum distance traveled by an EV on a full charge.

Range anxiety – Claimed to be the reason behind the birth of Tesla, it’s the fear of an EV driver that the vehicle would run out of charge before completing a trip. Over time, as one starts using an EV on a regular basis, the anxiety wanes but it’s seen as one of the biggest barriers to purchase an EV.

Internal Combustion Engine Vehicle (ICEV) – Vehicles, like your normal car or bike, are powered by the internal combustion of fuel like petrol or diesel.

State of Charge (SoC) – The level of energy present in a battery relative to its full capacity. The available drive range is derived from the current SoC in an EV.

Now that we’ve got the terms covered, let’s dig into the specifics of EV routing.

But first, how is EV routing any different from a usual vehicle routing problem?

Isn’t routing a common challenge for all automobiles?

You still peep into GMaps to know the fastest route to reach your office. So how is it any different for an electric vehicle?

Well, when an ICE vehicle is used to reach a certain destination, the driver would pick a route that saves time rather than a path that would cut back fuel consumption.

Switch gears to the mind of an EV driver. Here are some questions that would pop up instantly –

  • Will the charge stay till I get to the destination?
  • How much energy will be consumed in this route?
  • Are there charging stations en route?
  • How much time would I lose if I’ve got to charge?

Energy efficiency precedes the time factor for EV owners who are more concerned about the limited range of the vehicle and the lifespan of the battery. Studies reveal that EV drivers would opt for a route that minimizes energy consumption and save the worry and time taken to charge, though it would take a tad longer to reach their destination.

EV routing algorithms to the rescue

While normal vehicle routing algorithms decode the shortest path for ICE vehicles with time as the primary constraint, EV-specific routing algorithms need to weigh in a lot of additional constraints to arrive at an energy-efficient route.

Cracking the optimal route, EV routing algorithms have to consider the following factors –

Battery characteristics – The range you can cover relies on the battery’s current state of charge (SOC) and the number of charging stops is forecasted based on SoC. Battery degradation or health also determines how effectively it can hold a charge.

Driving style – Pumping on those brakes and accelerators hard or hitting a new high by touching those speed limits? Fun fact: Even for ICEs fuel consumption can be cut down with a decent driving style. No doubt, when energy consumption is our main criteria, the way you zip and zap through the lanes has a big impact on routing.

Traffic and Terrain – Dodging those bumps on suburban roads or cruising through highways, real-time road topography and traffic affect energy drain.

Recharging time and schedule – Till we have Superchargers around, a pit stop for EVs would be close to an hour with DC fast charging at a public charge point. So the waiting time and the detour (if needed) play a vital part while routing EVs, unlike ICEs that can be topped up anywhere on the go.

Attempts to address the electric vehicle routing problem (EVRP) began in 2010 when EV-specific constraints were observed, and modified algorithms were proposed. The contribution of every factor to the overall route scheme is still being studied extensively and workarounds are done by tweaking these algorithms.

Integrated GPS the way forward for energy optimal routing

Now that you clearly see why GMaps wouldn’t be enough to give an EV-specific energy optimal route, let’s turn to the other options in hand. Mobile apps for EV route planning are available in the market but have their own limitations of accuracy and usability.

Critical data from the vehicle including current SoC, driving patterns, and vehicle load that immensely influence the route prediction can’t be sourced by the apps and have to be manually entered every time you plan a trip. These details also have to be updated every time you stop for a battery recharge.

Independent routing apps also rely solely on your phone’s GPS which is prone to signal interruptions and could steer you in the wrong way.

Ouch! Missed that turn did you?

Turn-by-turn navigation for electric vehicles comes along with the challenge of finding charging stations in the vicinity to bate charging worries of the driver. An inaccurate GPS could easily throw an EV driver off balance when charging points are unavailable in alternative routes suggested after a missed turn.

So how exactly does an integrated GPS help in smart EV routing?

When a GPS sits ingrained in an electric vehicle, details such as battery SoC along with real-time and historical driving patterns are easily sensed and interleaved with traffic information to map out reliable routes.

The high precision of built-in GPS comes from its ability to detect vehicle position, speed, direction, and altitude even when GPS signals are weak. This accurate positioning is achieved through techniques like dead reckoning that take the vehicle’s last known position that’s merged with your vehicle’s wheel tick, gyroscope, and accelerometer data to pinpoint the exact vehicle location thus compensating the loss in GPS signals. Interpreting signals from multiple satellite systems instead of relying on just one further improves the availability and accuracy of the positioning system.

Since an integrated GPS holds data on the EV’s internals, driver stats like braking and accelerating patterns, and understands the lay of the land, it can put together an ideal driver profile to guide the driver. So the next time you go hard on the accelerator while running low charge, your navigator buddy would pop an alert reminding you to go easy on the pedal and save charge.

EV drivers will have the option to choose between an energy-optimal route or a time-saving route and also alternate between the two during the journey. Given the accuracy of the vehicle integrated GPS, estimated arrival times will be on the dot and routes can be updated quickly along with the charging stops to reduce charging worries. Charging stations would also be listed with wait times based on the EV’s supported connector type and battery technology.

Data sources for smart EV routing

Final thoughts

Innovative ideas are being implemented to break the barrier of range anxiety that prevents a vast majority of people from considering an EV. Take for example the on-route battery warm-up feature introduced by Tesla, where the EV inbuilt sat nav would sense that the vehicle is nearing a charge station and beginning heating up the battery so that the charge time is reduced. Pretty cool (or warm!), right?

EVs sounded alien a decade back, just like Fords did when horses prevailed. But you know how history played out. Technology is growing leaps and bound with connected cars becoming mainstream and eco-friendly vehicles being adopted better as people embrace sustainability.


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Maximizing the Value of Industrial IoT with Private Mobile Networks



Private mobile networks
Illustration: © IoT For All

There is no shortage of wireless technologies available for IoT deployments, particularly for industrial IoT and factory automation settings. LoRa, Bluetooth, LTE, Z-Wave, Zigbee, and Wi-Fi are all candidates used in commercial deployments today. However, given the reliability, performance, and coverage requirements for industrial IoT and automation applications, it’s clear that 5G is a superior connectivity solution for manufacturers and industrials. So much so that the 3GPP has “baked” time-sensitive networking requirements into its standards process.


When focusing on physical control applications across different vertical markets, especially industrial automation and energy automation, 5G is ideally suited to deliver more deterministic wireless connectivity. Many of today’s industrial automation and manufacturing floor applications can simply no longer tolerate any network delay or latency associated with conventional wireless solutions such as Wi-Fi. If latency is experienced, these applications often time out or stop working, often causing irreversible damage to business operations and loss of revenue and productivity.

New private 5G technology solves these problems with ultra-reliable ultra-low-latency communication (URLLC) capabilities now required for any mission-critical use cases that require 24/7 availability and need to share real-time information. However, how 5G is deployed in an industrial IoT setting is as important as its technology.


Thanks to the FCC’s recent decision to open up an unlicensed wireless spectrum in the CBRS (Citizens Broadband Radio Service) band, industrials interested in IoT now have the opportunity to deploy what’s known as a private mobile network.

This is very similar to the public cellular network that most of us use daily with our smartphones and tablets. Private mobile networks are built using the same 5G protocols, but the networks themselves are not owned and operated by wireless service providers like Verizon, AT&T, and others. A private 5G network is owned and operated by a single organization and geographically bound by that company’s property (like a smart factory) and managed similarly to its Wi-Fi networks today. The organization owns the equipment and data running over the network with complete control over all security and quality of service policies.

Private 5G Networks

Private 5G networks for IoT provide some critical capabilities that are not possible with other wireless technologies. Some of these include:

Enhanced Coverage

Private 5G networks are designed explicitly for the kind of network traffic generated by IIoT sensor networks. Moreover, private 5G networks give individual organizations far better control in designing and deploying a RAN (Radio Access Network) on their premise to ensure the ideal coverage for all applications. Private 5G networks are also ideal for outdoor or mixed indoor/outdoor applications.

Superior Reliability

IIoT use cases, devices, and systems need ultra-reliable connectivity to perform their core functions. From a wireless perspective, private mobile networks are the only option capable of delivering on that requirement.

Ultra-Low Latency

URLLC technologies inherent in 5G are augmented by private mobile network models, giving industrial organizations the ability to deploy applications that demand real-time communications. Use cases like smart monitoring for worker safety, robotics, and heavy equipment wouldn’t be feasible without this functionality.

Enhanced Security

The private 5G network model ensures that organizations have complete control over their data and do not rely on a public wireless operator to handle one of its most valuable resources. Another benefit of this new spectrum-based “traffic lane” is that it ensures the manufacturing data traffic is kept local and separate from networks used by guests or other personnel that do not need access to secure data. That built-in security can be a critical element for business and safety reasons.


There are multiple deployment options for private 5G networks. One of the most popular approaches is to “do it yourself” using purpose-built systems designed specifically for enterprise use. Enterprise can purchase the technology from the same supplier channels from which IIoT organizations consume other solutions. These include VARs, system integrators, and even managed service providers (MSPs).

Private 5G networks also afford organizations the rare ability to build the network on their own terms, integrating cellular technology with their existing IT infrastructure. This gives companies complete control over the organizations but does require some level of expertise internally.

Another less popular approach is contracting with a carrier or service provider that already operates a vast 5G public network infrastructure. In this case, companies are offered a “slice” of the public network virtually dedicated to them. This typically requires term contracts with a provider and relinquishes the control of the infrastructure to the operator. If something changes, a new application hits the networks, or some problem arises, the carrier is effectively charged with fixing the issue. When time is of the essence, enterprises must often wait on the carriers to resolve.

Use Cases

Because of its unique ability to overcome many of the inherent wireless problems associated with conventional wireless technologies, private 5G networks have begun to serve as the foundation for myriad IIoT use cases, including:

Autonomous Guided Vehicles (AGVs)

AGVs can be used for security, moving products, and many other applications. These can include wheeled robotic vehicles or even drones.

Computer Vision and Smart Monitoring Applications

In combination with machine learning, imaging is being applied to a wide range of applications. Worker safety and ensuring policy compliance are important to use cases. For example, a smart monitoring solution can ensure the appropriate amount of people are in a given area, monitor moving equipment, and guarantee that workers are wearing appropriate Personal Protective Equipment (PPE).

Predictive Maintenance

Private 5G networks can help identify metal fatigue or manufacturing faults to reduce failures and outages or determine when specific elements need to be replaced. The amount of data required by the HD cameras for this application can be huge and require a 5G connection with its high reliability and performance.

Remote Control of Heavy Equipment

Everything from cranes to earth-moving equipment to oil and gas pumps could benefit from a private 5G network. These applications are often outdoors, which requires the capabilities of 5G wireless in a private model.

These are just a few of the many applications that private 5G networks enable for the Industrial IoT.

Ultimately, based on 4G and 5G cellular wireless technology, emerging private mobile networks now offer a more robust and reliable connectivity option for a myriad of different industrial and manufacturing needs. While 5G on its own has been overhyped as the be-all, end-all for consumers, its deployment within the enterprise will profoundly impact the future of campus networks. Through the use and deployment of private mobile networks, IoT organizations can now gain immense value that translates into lower costs, improved productivity, and unprecedented security and control.

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Why Pairing IoT Devices to Things Must be Easy



Pairing IoT Devices
Illustration: © IoT For All

My father has fully embraced IoT integration into his everyday life. If you spent a day at my parent’s house, you’d notice that a significant number of their household functions are controlled digitally. A sliver of pure irony shines through when I, the millennial who works at an IoT software startup, can’t figure out how to turn on the living room lights. From the speaker system to the thermostat, to the fairy lights on the back porch, almost every digital device in that house can be controlled through Alexa or my dad’s smartphone. 

My father’s devotion to maximizing his smart home capacity isn’t so much an edge case but a good look into where many (privileged) houses and modern spaces are headed very soon.

Before his household was successfully established as a facsimile IoT hub, my dad had to connect each device to the wireless network, mobile device, and other devices. As a product designer in the IoT industry, that setup is a process of significant importance to me. Pairing IoT devices to things are something I often must account for when working on IoT solutions. I would be remiss if I didn’t take a moment to thank the brave UX pioneers before me who tackled the very first IoT device pairings and set the standards for what does and doesn’t work.

Several key factors come into play when designing a fluid and easy-to-comprehend pairing journey. For starters, you must take into account what kind of hardware you’re working with. When assessing the hardware, there are ways you can configure a device to communicate a message, even when that device doesn’t have a physical screen. Sensors can often be built with small lights to communicate connectivity status. For example, take a look at your router or modem for an example. You should see several blinking or solid lights, each relaying a different message about the status of your device’s connectivity or signal strength.  

When it comes to device setup and pairing, you also have to consider whether the goal is a single item pairing or if you want the ability to batch associate your devices. For example, connecting a wireless speaker to your mobile device is a one-time association. Once it is up, the devices should remember one another and result in easy pairing for as long as you have them. Of course, you want to create a simple and concise experience for setting up your wireless speaker on your phone. Still, since this isn’t going to be a repeat action, there isn’t a massive amount of pressure on the designer to make sure it can be done in one or two clicks maximum. 

On the other hand, there are scenarios in which repeat association makes more sense. For example, you may have a person associating trackers with hundreds of cars per day in a vehicle monitoring solution. In this case, your goals as a designer might pivot a bit to account for a quicker association process to avoid user frustration. 

In retail IoT solutions, the pairing process plays a significant role in whether or not the product sells. It is increasingly common that someone will purchase a smart device, excited for the accessibility boost it has promised to provide, only to abandon the device altogether due to a frustrating setup experience. More often than not, people also do not have the spare time or patience to call a customer representative to walk them through the setup. 

However, it increases the cost for the producer, who must staff and maintain a customer support team that meets this demand for the ones that do make that call. Establishing a comprehensible and fluid pairing setup process for your product will remove this burden from both consumer and producer.

Since IoT solutions often promise increased accessibility, the pairing process for these devices should follow suit. Anyone should pair IoT devices to their networks, other devices, etc., regardless of their technical background. Pairing IoT Devices to things must be easy because it will soon become a universal action as IoT devices further intertwine with household items. Even the least technologically familiar person should follow the instructions on the screen to associate their smart device to their network and other devices. 

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Bugs in NVIDIA’s Jetson Chipset Opens Door to DoS Attacks, Data Theft



The administrator of your personal data will be Threatpost, Inc., 500 Unicorn Park, Woburn, MA 01801. Detailed information on the processing of personal data can be found in the privacy policy. In addition, you will find them in the message confirming the subscription to the newsletter.

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When Is Free Really Free? Making Sense of Open Source IoT Platforms



open source IoT
Illustration: © IoT For All

When there’s more than one open-source IoT platform out there, how do you evaluate the one that best fits your needs? What are some common pitfalls to avoid? This article provides a brief overview of the top contenders, with their strengths and weaknesses.

Open Source Relevance

Open source means you are free to use, modify, combine or compile software code in any way you want, without any obligation, as long as you don’t redistribute it using hardware or web services. If you want to embed open source code in your OEM product or service, different options are available based on the type of open source license.

Open Source is relevant because you are not tied to the supplier of the code, thus preventing any unwanted vendor lock-in. Having full access to the source code, you have the flexibility to adjust to changing market conditions and extend, change or pivot when needed. Moreover, you have the ability to add or optimize functionality for your product.

If the code is free, how do open source IoT developers make money? The way most companies make money with open source software is with add-ons and support services. This ranges from paid-for advanced features, organizing a hosted service (SaaS) to project management or support and maintenance for commercial users.

Selecting the Best Open Source Platform

To identify the right open-source IoT platform for your needs, consider the following additional criteria based on organizational needs, quality, and legal concerns:

  • Must have functionalities: IoT platforms require a coherent set of functionalities which include the ability to integrate through multiple protocols, use automation, provide data visualizations, use edge gateways, multi-tenancy, as well as provide a front-end strategy and account management and identity services.
  • Professional implementations: the extent to which the platform has been adopted by larger organizations is a good signal pointing to the quality of the IoT solution.
  • Community backing: is there an active community of users? Watchers and star-gazers are nice, but active contributors are what moves the needle. How recent are code commits to the projects, and is their activity in your region?
  • User-friendliness: The flexibility to tailor the code to specific applications is paramount. Great user-friendliness also entails comprehensive documentation and community support.
  • Level of open source: Which parts of the IoT platform are open source? Watch out for “bait and switch” offerings where the company’s open-source offering is, in reality, a stripped-down version of their higher-functionality for-pay product. Closely review possible code-use restrictions, such as features that are only available with a for-pay license. 
  • Professional backing and licensing: Does the open-source entity provide clear copyright and the ability to get a commercial license? Is the copyright owner well-structured and legally sound? This is relevant for professional entities who want to integrate the software as part of their commercial offering and seek long-term professional support.

Top Open Source IoT Platforms

FIWARE is especially popular in Europe and South America. It is professionally backed by Atos, Engineering, NEC, and Telefonica. On the non-profit side, it has the support of the Open Agile and Smart Cities communities. As a whole, it’s solid as a networked organization. However, potential users need to be aware that Fiware is not a single product but a larger series of projects. This makes it hard to use in open source as it is extremely complex and CPU-intensive to deploy into a unified, complete product. 

OpenBalena is not a complete IoT platform, merely a device orchestration tool that allows you to manage many devices in the field. It’s a complementary function to all of the other IoT Platforms. Its commercial version ‘BalenaCloud’ is used by many, while the open-source version is somewhat limited, as it uses a simple command-line editor and misses some relevant features and documentation, such as querying your installed base.

Thinger was developed as a complete and friendly solution for small project users, with a few platform integrations. However, with their move to a more extensive pricing plan where features such as MQTT support or dashboard branding are not available for ‘makers’ means, it is no longer completely open source.

Thingsboard has gained significant traction and is backed by investors. It managed to develop an extensive library of visualization widgets and has recently introduced a horizontally scaling solution. Like Thinger, it pushes advanced features from the open-source into a paying commercial model. This IoT platform is most popular with smaller companies.

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