ObjectBox Recognized as a Sustainable Profitable Tech Solution by the Solar Impulse Foundation

ObjectBox Recognized as a Sustainable Profitable Tech Solution by the Solar Impulse Foundation

ObjectBox is proud to be officially recognized as a sustainable and efficient solution by the Solar Impulse Foundation. Although we have self-identified as a #sustainabletech company since our induction, we’re proud to be recognized as an “efficient, clean and profitable solutions with a positive impact on environment and quality of life,” after taking part in an in-depth technical and business evaluation with the team at the Solar Impulse Foundation.

Empowering tech innovation

This label recognizes that ObjectBox empowers innovation with a highly efficient and sustainable technology. The Solar Impulse Efficient Label identifies sustainable tech solutions from around the world to help companies choose their tech stack responsibly.  

solar-impulse-foundation-label-sustainable-software-for-the-edge

UN Sustainable Development Goals

All Solar Impulse awardees contribute to one or several of the UN Sustainable Development Goals; ObjectBox received the globally recognized label for supporting three of the Solar Impulse focused initiatives: 

  • Affordable and Clean Energy: ObjectBox
  • Clean Water and Sanitation
  • Industry, Innovation and Infrastructure : ObjectBox
  • Sustainable Cities and Communities: ObjectBox
  • Responsible Consumption and Production

How is ObjectBox sustainable?

objectbox-local-data-sustainable

ObjectBox enables scalable and sustainable digitalization with a high performance edge database solution and synchronization solution. The ObjectBox database empowers local data storage, while ObjectBox Sync reduces unnecessary data traffic. ObjectBox is therefore ideally suited for efficient, useful, and sustainable Edge Computing. 

Comparing the transmission of the same data sets, ObjectBox saves 20-60% on transmission data volume. By combining delta syncing with efficient compression based on standard and proprietary edge compression methods to keep data small, ObjectBox can reduce device energy consumption and thus CO2 emissions for data transmissions.

As our digital world grows, we all need to do what we can to structure these digital environments in an efficient and sustainable way. ObjectBox helps reduce digital waste. Digital waste unnecessarily burdens bandwidth infrastructure and fills cloud servers, forcing the expansion of cloud farms and in turn, contributing to the pollution of the environment. Therefore, we are excited to be part of the 1000solutions program.

Dr. Vivien Dollinger

CEO and Co-founder, ObjectBox

What does it mean to get a Solar Impulse Label? 

The Solar Impulse Label: a label focused on both the environment and profitability

The first label to assess the economic profitability of products or processes that protect the environment. The Solar Impulse Efficient Solution Label is attributed following a strict selection process performed by external independent experts. By ensuring high standards of sustainability and profitability, this internationally recognized label is considered as a credible marker of quality for solution seekers in business and governments, facilitating their sourcing of solutions to reach environmental commitments.

About the Solar Impulse Foundation

The Solar Impulse Foundation aims to identify clean, efficient and profitable solutions in order to accelerate their implementation and the transition to a sustainable economy. Thanks to the awarding of a label with high standards of sustainability and profitability, the Foundation can support political and economic decision-makers in their efforts to achieve their environmental targets and encourage them to adopt more ambitious energy regulations, necessary for implementation at large-scale of these solutions on the market. A way to take the success of the first round-the-world solar flight further.

white-leaf

Interesting in finding out how ObjectBox can make your edge computing project more sustainable?

How Building Green IoT Solutions on the Edge Can Help Save Energy and CO2

How Building Green IoT Solutions on the Edge Can Help Save Energy and CO2

The internet of things (IoT) has a huge potential to reduce carbon emissions, as it enables new ways of operating, living, and working [1] that are more efficient and sustainable. However, IoT’s huge and growing electricity demands are a challenge. This demand is due primarily to the transmission and storage of data in cloud data centers. [2] While data center efficiency and the use of green energy will reduce the CO2 emissions needed for this practice, it is not addressing the problem directly. [3

iot-data-cloud-energy-waste

With ObjectBox, we address this unseen and fast-growing CO2 source at the root: ObjectBox empowers edge computing, reducing the volume of data transmitted to central data storage, while at the same time, heightening data transmission and storage efficiency. [4] We’ve talked before about how edge computing is necessary for a sustainable future, below we dive into the numbers a bit deeper. TLRD: ObjectBox enables companies to cut the power consumption of their IoT applications, and thus their emissions, by 50 – 90%. For 2025, the potential impact of ObjectBox is a carbon emission reduction of 594 million metric tons (see calculations below).

How ObjectBox’ Technology Reduces Overall Data Transmission

 ObjectBox reduces data transmission in two ways: 1. ObjectBox reduces the need for data transmission, 2. ObjectBox makes data transmission more efficient. ObjectBox’ database solution allows companies to build products that store and process data on edge devices and work with that data offline (as well as online). This

Green IoT Solution

not only improves performance and customer experience, it also reduces the overall volume of data that is being sent to the cloud, and thus the energy needed to transfer the data as well as store it in the cloud. ObjectBox’ Synchronization solution makes it easy for companies to transmit only the data that needs to be transmitted through 1) selective two-way syncing and 2) differential delta syncing. Synchronizing select data reduces the energy required for unnecessarily transmitting all data to the cloud.

We have demonstrated in exemplary case studies that ObjectBox can reduce total data transmissions by 70-90%, depending on the case. There will, however, typically be value in transmitting some parts of data to a central data center (cloud); ObjectBox Sync combines efficient compression based on standard and proprietary edge compression methods to keep this data small. ObjectBox also has very little overhead. Comparing the transmission of the same data sets, ObjectBox saves 40-60% on transmission data volume through the delta syncing and compression, and thus saves equivalent CO2 emissions for data transmissions. Additional studies support these results, and have shown that moving from a centralized to a distributed data structure, saves between 32 and 93% of transmission data. [5

sync-sustainable-data-save-energy

Calculations: How Does ObjectBox Save CO2?

Physically using a device consumes little energy directly; it is the wireless cloud infrastructure in the backend (data center storage and data transmission) that is responsible for the high carbon footprint of mobile phones [6] and IoT devices. Estimates say that IoT devices will produce around 2,8 ZB of data in 2020 (or 2,823,000,000,000  GB), globally. [7] Only a small portion of that data actually gets stored and used; we chose to use a conservative estimate of 5% [8] (141,150,000,000 GB) and of that portion, 90% is transferred to the cloud [9] (127,035,000,000 GB). Transferring 1 GB of data to the cloud and storing it there costs between 3 and 7 kWh. [10] Assuming an average of 5 kWh this means a 127,035,000,000 GB multiplied by 5kWh, resulting in a total energy expenditure of 635,175,000,000 kWh. Depending on the energy generation used, CO2 emissions vary. We are using a global average of 0,475 kgCO2 / 1 kwH. [11] In total this means that there will be 301,708,125,000 KG of CO2, or roughly 301 million metric tons of CO2 produced to transfer data to the cloud and store it there in 2020. 

Projections for 2025 have data volumes as high as 79.4 ZB. [12] Following the same calculations as above, IoT devices would be responsible for 8 billion metric tons of CO2 in 2025.* We estimate that using ObjectBox can cut CO2 caused by data transmission and data centers by 50-90%, by keeping the majority of data on the device, and transmitting data efficiently. It will take time for ObjectBox to enter the market, so assuming a 10% market saturation by 2025 and an average energy reduction of 70%, using ObjectBox could cut projected CO2 emissions by 594 million metric tons in 2025.

ObjectBox is on a mission to reduce digital waste which unnecessarily burdens bandwidth infrastructure and fills cloud servers, forcing the expansion of cloud farms and in turn, contributing to the pollution of the environment. As our digital world grows, we all need to give some thought to how we should structure our digital environments to optimize and support useful, beneficial solutions, while also keeping them efficient and sustainable. 

*Of course, in that time, the technologies will all be more efficient and thus use less electricity while at the same time CO2 emissions / kWh will have dropped too. Thus, we are aware that this projection is an oversimplification of a highly complex and constantly changing system.

[1] https://www.theclimategroup.org/sites/default/files/archive/files/Smart2020Report.pdf
[2] https://www.iea.org/reports/tracking-buildings/data-centres-and-data-transmission-networks
[3]“Data centres… have eaten into any progress we made to achieving Ireland’s 40% carbon emissions reduction target.” from https://www.climatechangenews.com/2017/12/11/tsunami-data-consume-one-fifth-global-electricity-2025/
[4] https://medium.com/stanford-magazine/carbon-and-the-cloud-d6f481b79dfe
[5] https://www.researchgate.net/publication/323867714_The_carbon_footprint_of_distributed_cloud_storage
[6] https://www.resilience.org/stories/2020-01-07/the-invisible-and-growing-ecological-footprint-of-digital-technology/
[7] https://www.idc.com/getdoc.jsp?containerId=prUS45213219, https://priceonomics.com/the-iot-data-explosion-how-big-is-the-iot-data/, https://www.gartner.com/en/newsroom/press-releases/2018-11-07-gartner-identifies-top-10-strategic-iot-technologies-and-trends, https://www.iotjournaal.nl/wp-content/uploads/2017/02/white-paper-c11-738085.pdf, ObjectBox research
[8] Forrester (https://internetofthingsagenda.techtarget.com/blog/IoT-Agenda/Preventing-IoT-data-waste-with-the-intelligent-edge), Harvard BR (https://hbr.org/2017/05/whats-your-data-strategy), IBM (http://www.redbooks.ibm.com/redbooks/pdfs/sg248435.pdf), McKinsey (https://www.mckinsey.com/business-functions/mckinsey-digital/our-insights/the-internet-of-things-the-value-of-digitizing-the-physical-world)
[9] https://www.gartner.com/smarterwithgartner/what-edge-computing-means-for-infrastructure-and-operations-leaders/
[10] According to the American Council for an Energy-Efficient Economy: 5,12 kWh of electricity / GB of transferred data. According to a Carnegie Mellon University study: 7 kWh / GB. The American Council for an Energy-Efficient Economy concluded: 3.1 kWh / GB.
[11] https://www.iea.org/reports/global-energy-co2-status-report-2019/emissions
[12] https://www.idc.com/getdoc.jsp?containerId=prUS45213219

Introducing: ObjectBox Generator, plus C++ API [Request for Feedback!]

Introducing: ObjectBox Generator, plus C++ API [Request for Feedback!]

We are introducing the ObjectBox Generator today to simplify ObjectBox development for more programming languages, starting with C/C++. Additionally, we are releasing a brand new C++ API that goes hand in hand with the new generator. Historically, our C API was rather low level as it was focused on providing the foundation for our Swift and Go APIs. With this release we want to provide C/C++ developers with ObjectBox convenience and ease of use. 

ObjectBox Generator takes over the burden of writing the binding code and data model declaration. Based on a single input file, it generates the code for you, so you can focus on the actual application logic.

Generator Example

ObjectBox let’s you handle data as FlatBuffers. For example, you can put and get data objects as FlatBuffers encoded bytes. To work with FlatBuffers, you need to define a FlatBuffer schema file (.fbs). And this file is also the input for ObjectBox Generator. This way, everything is defined in a single location.

Let’s say we have a FlatBuffers schema file “task.fbs” with the following content:

Now, we can tell ObjectBox Generator to use this file to generate C++ sources:

This makes ObjectBox Generator to generate the following files:

  • objectbox-model.h: source code to build the internal data model, that you need to pass when creating a store.
  • objectbox-model.json: keeps track of internal schema IDs; you don’t need to worry about this except that you should put it in your source control.
  • task-cpp.obx.h: the C++ value structs (data objects), binding code for FlatBuffers and the new Box class.

C++ API Example

Now, let’s use the previously generated code and the new C++ API around the Store and Box classes. A simple CRUD application boils down to a few lines:

Note that the generated code is header-only and compatible with the existing ObjectBox C-API, allowing both to be used from the same application. The C and C++ APIs both have unique advantages: the C++ API uses RAII so you do not need to worry about cleaning up, while the C API has additional features, e.g. queries.

Open Source, Docs

ObjectBox Generator is open source and available on GitHub. The repository comes with a readme file that also serves as a documentation. Among other things, you will find ObjectBox specific annotations there, which are used in fbs files to express ObjectBox-specific concerns. For example, in the definition of Task above, we used ulong as a FlatBuffers type to store dates. However, FlatBuffers does not know what a date is and we use ObjectBox annotations to express this:

For our initial release of ObjectBox Generator and the public C++ API we decided on labeling it as version 0.9. Although we are already very close to a 1.0 and we wanted to gather some feedback before our first major release. As we can still change the API or smooth out any rough edges you may find, we cannot stress enough how much we welcome and appreciate your feedback at this point. Thank you!

Why do we need Edge Computing for a sustainable future?

Why do we need Edge Computing for a sustainable future?

Centralized data centers consume a lot of energy, produce a lot of carbon emissions and cause significant electronic waste. While data centers are seeing a positive trend towards using green energy, an even more sustainable approach (alongside so-called “green data centers” [1]) is to cut unnecessary cloud traffic, central computation and storage as much as possible by shifting computation to the edge. Ideally, an Edge Computing strategy harnesses the power of already deployed available devices (like e.g. smartphones, machines, desktops, gateways), making the solution even more sustainable.

Why do Digitisation and IoT projects need to think about sustainability now?

Huge centralized data centres (cloud computing) have become a critical part of the infrastructure for a digitalized society. These large central cloud data centers produce a lot of carbon emissions, electric and electronic waste. [2] The share of global electricity used by data centres is already estimated to be around 1-3% [3] and data centers generate 2% of worldwide CO2 emissions (on par with the aviation industry). [4]

54% of which are caused by the cloud data centers of the big hyperscalers (Google, Amazon, Microsoft, Alibaba Cloud). [5] On top of this, providing and maintaining cloud infrastructure (manufacturing, shipping of hardware, buildings and lines) also consumes a huge amount of greenhouse gases [3] and produces a lot of abnormal waste (e.g. toxic coolants) at the end of life. [6]

sustainable edge computing

Bearing that in mind, the growth forecasts for digitization, IoT, and Mobile [7] are concerning. The steady increase in data processing, storage, and traffic in the future, comes with a huge electricity demand for this industry. [8] In fact, estimations expect the communications industry to use 20% of all the world’s electricity by 2025. [9]

sustainable edge computing

Shifting to green energy is a good step. However, a more effective and ultimately longer term solution requires looking at the current model of data storage, filtering, processing and transferal. By implementing Edge Computing, we can reduce the amount of useless and wasteful data traversing to and from the cloud as much as possible, thus reducing overall energy requirements in the long term.

What is Edge Computing?

While until recently 90 percent of enterprise data was sent to the cloud, this is changing rapidly. In fact, this number is dropping to only 25 percent in the next 3 years according to Gartner. By then, most of the data will be stored and used locally, on the device it was created on, e.g. on smartphones, cars, trains, machines, watches. This is called Edge Computing. Accordingly, edge devices need the same technology stack (just in a much smaller format) as a cloud server. This means: An operating system, a data storage / persistence layer (database), a networking layer, security functionalities etc. that run efficiently on restricted hardware.

As you can only use the devices’ resources, which can be pretty limited, inefficient applications can push a device to its limits, leading to slow response rates, crashes, and battery drain.

edge device architecture

EDGE DEVICE ARCHITECTURE

Edge Computing is much more than some simple data pre-processing, which takes advantage of only a small portion of the computing that is possible on the edge. An on-device database is a prerequisite for meaningful Edge Computing. With an on-device database, data can be stored and processed on the devices directly (the so called edge). Only useful data is sent to the server and saved there, reducing the networking traffic and computing power used in data centers tremendously, while also making use of the computing resources of devices which are already in use. This greatly reduces bandwidth and energy required by data centers. On top, edge computing also provides the flexibility to operate independent from an Internet connection, enables fast real time response rates, and cuts cloud costs.

Why is Edge Computing sustainable?

Edge Computing reduces network traffic and cloud data center usage

With Edge Computing the amount of data traversing the network can be reduced greatly, freeing up bandwidth. Bandwidth refers to the transmission speed of data on the network. While maximum speeds are published by the network operators, the actual speed obtained in a given network is almost always lower, because the bandwidth is shared and limited. The more data transferred at any given moment, the slower the network speed. Data on the edge is also much more likely to be used, and then (due to restricted devices size) deleted when it is no longer useful.

Edge computing is optimized for efficiency

Edge “data centres” are typically more efficient than cloud data centres. As described above, resources on edge devices are restricted – as opposed to cloud infrastructure, edge devices do not scale horizontally. Therefore, every piece of the tech stack is – ideally – highly optimized for resource efficiency. Any computing done more efficiently helps reduce energy consumption, especially taking into account the huge number of devices already deployed (number), the worldwide impact is significant.

With Edge Computing you can put already deployed hardware to better use

On top, there is a realm of edge devices already deployed that is currently underused. Many existing devices are capable of fairly complex computing; when these devices send all of their data to the cloud, an opportunity is lost. Edge Computing utilizes existing hardware and infrastructure,  taking advantage of the existing computing power. If these devices continue to be underused, we will need to build bigger and bigger central data centers, simultaneously burdening existing network infrastructure and reducing bandwidth for senselessly sending everything to the cloud.

Cloud versus Edge: an Example

Today, many projects are built based on cloud computing. Especially in first prototypes or pilots, cloud computing offers an easy and fast start. However, with scale, cloud computing often becomes too slow, expensive, and unreliable. In a typical cloud setup, data is gathered on edge devices and forwarded to the cloud for computation and storage. Often a computed result is sent back. In this design, the edge devices are dumb devices that are dependant upon a working internet connection and a working cloud server; they do not have any intelligence or logic of their own. In a smart home cloud example, data would be sent from devices in the home, e.g. a thermostat, the door, the TV etc. to the cloud, where it is saved and used.

Cloud vs Edge

If the user would want to make changes via a cloud-based mobile app when in the house, the changes would be send to the cloud, changed there and then from there be sent to the devices. When the Internet connection is down or the server is not working, the application will not work.

With Edge Computing, data stays where it is produced, used and where it belongs – without traversing the network unnecessarily. This way, cloud infrastructure needs are reduced in three ways: Firstly, less network traffic, secondly, less central storage and thirdly less computational power. Rather, edge computing makes use of all the capable hardware already deployed in the world. E.g. in a smart home, all the data could stay within the house and be used on site. Only the small part of the data truly needed accessible from anywhere would be synchronized to the cloud.

Cloud vs Edge

Take for example a thermostat in such a home setting: it might produce 1000s of temperature data points per minute. However, minimal changes typically do not matter and data updates aren’t necessary every millisecond. On top, you really do not need all this data in the cloud and accessible from anywhere.

With Edge Computing, this data can stay on the edge and be used within the smart home as needed. Edge Computing enables the smart home to work fast, efficiently, and autonomous from a working internet connection. In addition, the smart home owner can keep the private data to him/herself and is less vulnerable to hacker attacks. 

How does ObjectBox make Edge Computing even more sustainable?

ObjectBox improves the sustainability of Edge Computing with high performance and efficiency: our 10X speed advantage translates into less use of CPU and battery / electricity. With ObjectBox, devices compute 10 times as much data with equivalent power. Due to the small size and efficiency, ObjectBox runs on restricted devices allowing application developers to utilize existing hardware longer and/or to do more instead on existing infrastructure / hardware.

Alongside the performance and size advantages, ObjectBox’ Sync solution takes care of making data available where needed when needed. It allows synchronization in an offline setting and / or to the cloud. Based on efficient syncing principles, ObjectBox Sync aims to reduce unnecessary data traffick as much as possible and is therefore perfectly suited for efficient, useful, and sustainable Edge Computing. Even when syncing the same amount of data, ObjectBox Sync reduces the bandwidth needed and thus cloud networking usage, which incidentally reduces cloud costs.

Also coming soon ObjectBox time series which will provide users an intuitive dashboard to see patterns behind the data. It will further help users to track thousands of data points/second in real-time

How Edge Computing enables new use cases that help make the world more sustainable

As mentioned above, there are a variety of IoT applications that help reduce waste of all kinds. These applications can have a huge impact on creating a more sustainable world, assuming the applications themselves are sustainable. Three powerful examples to demonstrate the huge impact IoT applications can have on the world:

1) Smart City Lighting: Chicago has implemented a system which allows them to save approx. 10 million USD / year and London estimates it can save up to 70% of current electricity use and costs as well as maintenance costs through smart public lighting systems. [10]

2) Reducing Food Waste: From farm to kitchen, IoT applications can help to reduce food waste across the food chain. Sensors used to monitor the cold chain, from field to supermarket, can ensure that food maintains a certain temperature, thus guaranteeing that products remain food safe and fresh longer, reducing food waste.

3) Reduce Water Waste: Many homes and commercial building landscapes are still watered manually or on a set schedule. This is an inexact method of watering, which does not take into account weather, soil moistness, or the water levels needed by the plant. Using smart IoT water management solution, landscape irrigation can be reduced, saving water and improving landscape health.

These positive effects are all the more powerful when the IoT applications themselves are sustainable. 

The benefits of cloud computing are broad and powerful, however there are costs to this technology. A combination of green data centers and Edge Computing helps to resolve these often unseen costs. With Edge Computing we can reduce the unnecessary use of bandwidth and server capacity (which comes down to infrastructure, electricity and physical space) while simultaneously taking advantage of underused device resources. ObjectBox amplifies these benefits, with high performance on small devices and efficient data synchronization – making edge computing an even more sustainable solution.

How EV Charging Benefits from Edge Computing

How EV Charging Benefits from Edge Computing

Edge computing allows data to be stored and used on local devices. Integrating Edge Computing directly within electric vehicle charging infrastructure improves station usability and also allows for real-time energy management.

Car charging and electric vehicles

The era of electric vehicles (EV) is coming: Already one in every 250¹ cars on the road is electric. While it is uncertain when electric vehicles will overtake traditional combustion engine vehicles, electric is clearly the future. Car charging infrastructure is critical for electric vehicle expansion – and one of the largest bottlenecks to EV adoption. Range anxiety is still one of the primary concerns for potential EV customers,² and charging station proliferation is still far behind traditional gas stations.

EV charging

State of the electric vehicle charging Market

The electric vehicle charging infrastructure market is still very divided, with many players vying for this large-growth sector – some predictions forecast over 40% CAGR for the car charging infrastructure market in the coming years.³ Car manufacturers, gas & oil, OEMs, and utilities companies (e.g. Tesla, VW, BMW, Shell, GE, Engie, Siemens, ABB) are actively taking part in the development of the market, recognizing the need to support future EV customers and the huge growth potential. Startups in the space like EcoG, Wirelane, flexEcharge and Elli offer solutions that focus on accessibility, efficiency and improving end user experiences.

Why Car Charging Stations need Offline Capability (Edge Computing)

First, let’s look at the challenges a vehicle charging provider needs to solve from a basic data perspective: Customers interfacing with charging stations require an account linked with basic information and payment methods. In order to charge a car, the user needs to be verified by the charging station, and is often required to have a pre-booked charging slot. Typically, a user would create a new account via a website or mobile phone beforehand, but not on the spot at the car charging station. Also booking slots are handled via a mobile app or website. However, the car charging station needs this information to allow a car to be charged.

This is only the most basic necessity. In the future, charging stations will provide more services to users, e.g. identifying users preference like cost over speed of charging, or choosing to charge with green energy. 

Depending on where the car charging station sits, it can be offline more or less often, e.g. in France there are quite many electric car charging stations in the country site, where the connection is typically flaky – and might not be available for days. On the other hand, there are stations that reside within a parking house or hotel and use a fixed land line for connectivity. In the latter case, your uptime can be very consistent, but typically you cannot guarantee the car charging station will be connected.

If the charging station tries to access this data only when it needs it, because a car is trying to charge, it may or may not have an internet connection at the time and thus the likelihood of failure is rather high. Accordingly, any new information should be pushed to the car charging stations when a connection is available and stored on the station. The hardware of a car charging station is capable enough to hold a lightweight database and persist data as is needed and useful.

EV charging edge computing solution

Choosing a data persistence layer (database) over a simple caching ensures not only that no data is lost, but can also allow more processing to happen on the station and allows for autonomous reactions. In combination with edge synchronization, which enables persistence layers to synchronize between car charging stations (that share a data space), fast data persistence allows for efficient load balancing as well as easily updating the configurations of all car charging stations.

 

Smart Energy Load Management – the need for fast response on the Edge

Managing energy is one of the greatest challenges for EV infrastructure providers. The difficulty here is less about overall energy consumption increasing – rather managing, predicting and preparing for high-demand peaks. Imagine everyone needs charging during a large public event, or at charging stations during holiday travel times – peak demands like these need to be anticipated and planned for. The future with electric cars needs to balance demand with a combination of smart chargers, efficient energy grid management, Vehicle-to-Grid (V2G) solutions, and perhaps even on-site batteries at larger charging stations to improve time-to-charge and optimize for electricity prices.

EV charging edge computing solution

Edge computing will play an important role in providing real-time, accurate energy load control, necessary for maintaining grid stability, particularly in emergency situations.⁴ At charging stations where many EVs plug in, smart edge nodes can balance charge schedules in real-time, optimizing based on EV owner requirements without overloading local transformers.⁵  On a larger scale, smart energy meters can use real-time edge computing to shift energy quickly to high-demand locations, cutting energy from low-priority appliances, limiting charge speeds, or pulling excess energy from V2G networks.

Thinking about energy management, the conversation fluidly moves from EV charging infrastructure to thinking about smart mobility, utilities, and smart city infrastructure on a larger scale. Car charging systems will be complex, interconnected and will progress in alignment with other ongoing digitization efforts to create data drive infrastructure across cities and the world. Edge computing, and base technologies like ObjectBox that enable working on the edge, are important enablers to ensure that real-time computing can happen anywhere and digitization is affordable, scalable, and sustainable.