
Green streaming is a set of techniques that enable a more sustainable and energy efficient streaming workflow from content production to playback.
As underlined in our CTV trends overview and according to the International Energy Agency’s (IEA) 2022 report, data centers and transmission networks that facilitate streaming account for 1-1.5% of the world’s total electricity consumption and 1% of the planet’s total energy-related GHG emissions.
To give a measure of comparison, In 2022 aviation accounted for 2% of global energy-related CO2 emissions (www.iea.org).
So no surprise the word green streaming is on media industry professionals’ lips more and more as well as the attempt to find more sustainable solutions.
But what can be done concretely to decrease emissions from the streaming supply chain?
From an ad insertion perspective, we optimized our SSAI platform Serverside.ai that with our new infrastructure Poseidon is even twice as efficient as before (contact us if you want to know more).
That said, apart from ad insertion, what other elements should content producers and distributors pay attention to and how to raise awareness among viewers as well?
We tried to answer these questions together with our friends at Fraunhofer FOKUS research institute and here is what emerged.
Table of Content
Green Streaming: Breaking Down the Streaming Value Chain

“The streaming supply chain ranging from content creation to display video on user screens is complex, with effects like scaling, concurrent viewers or distribution playing a crucial role and significantly influencing overall considerations”, says Robert Seeliger, Senior Project Manager and Video Sustainability Lead at Fraunhofer FOKUS. “To understand these interconnections and their effects”, he continues, “it is essential to measure and analyze energy consumption along the whole supply chain.”
And so they are doing for their green streaming research project, which is still in progress but has already led to some interesting discoveries. For example, if bitrate and resolution in video streaming have low impact on the energy consumption of smart TVs and other streaming devices for which the real energy-saving potential comes from the display and device settings, showing a direct correlation with the content brightness, there are still ways for content producers/distributors to save energy across the rest of the value chain.
That is why we collected some green streaming best practices we will report in the following sections.

First things first, when we are mentioning the streaming value chain or workflow, we are talking about a process that can be divided into the following parts:
Content production: developing content ideas/scripts, preparing and planning (pre-production), filming or recording (production), editing and adding effects (post-production).
Data encoding & packaging: converting raw video and audio files into a compressed format using codecs to reduce file size while maintaining quality, formatting the encoded content into streamable units, segmenting it into small chunks and preparing it with metadata for adaptive bitrate streaming.
Distribution: delivering content to users through Content Delivery Networks (CDNs), which use servers to efficiently route and cache data; optimizing and storing content in data centers to ensure fast and reliable access.
Playback: receiving, decoding, and displaying streaming media on users’ devices in real-time; dynamically adjusting video quality based on network conditions and ensuring a seamless viewing experience.
Having clarified this, we can move on to analyze the effective approaches to limiting the environmental impact of streaming activities.
Green TV Production

Green streaming practices related to the production phase focus on minimizing environmental impact through a combination of physical and virtual production techniques. Here is how this can be achieved:
Build Eco Friendly and Energy-Efficient Studios
Build sets using sustainable materials that can be reused or recycled.
At the same time, make good use of technology by implementing virtual sets and augmented reality (e.g., green screens) to reduce the physical assets needed for production.
Regarding energy consumption, on set and in the offices deploy LED lights instead of traditional lighting and use management systems that monitor energy usage to optimize efficiency.
Switch to Hybrid Production
Ulster University researchers highlighted the significant environmental benefits of virtual production and outlined how it can reduce carbon emissions by between 20% to 50% or higher compared to traditional film methods. This includes significant reduction of travel and on-site fuel costs which currently account for half of the industry’s carbon footprint.
So the best practices would be for filming to combine on-location shooting with remote or virtual production and to prefer digital tools and cloud-based workflows for pre-production (meetings, writing, etc.) and post-production (editing, storage, etc.).
Reduce Waste and Offset
As stated, virtual sets can reduce the amount of materials needed for filming, consequently also the amount of trash produced.
Another good practice is using digital scripts and documents to limit paper waste.
That said, rules are always the same for every industry so give new life to what you used by implementing comprehensive recycling programs and compensate for what you can not reduce by investing in carbon offset programs that involve the plantation of trees for example.
Educate and Improve
Train your employees and crew members on sustainable practices and the importance of reducing environmental impact. At the same time, track and report on the emissions related to production activities to identify areas for improvement and use these data to continuously improve green practices in future productions.
In summary, green streaming practices in hybrid production environments involve using energy-efficient technologies, promoting remote and virtual workflows, minimizing waste, using sustainable materials, and continuously monitoring and improving sustainability efforts. This approach helps reduce the environmental impact of media production while maintaining high production quality.
Green Data Encoding and Packaging

Green streaming practices related to data encoding and packaging focus on making the streaming process more efficient to reduce energy consumption and bandwidth usage. Here is how content-aware encoding and AI models can help:
Deploy Content-Aware Encoding
Content-aware encoding involves optimizing the encoding process based on the specific characteristics of the video content to achieve higher compression efficiency without sacrificing quality.
Use Proper Hardware/Software: Major energy saving potential in the encoding space lays in the type of infrastructure providers are using. For this reason, there is a trend from CPU based encoding towards usage of hardware accelerated processing like GPUs (NVENC/AMD VCE) in data centers combined with powerful CPUs as AMD EPYC. Even more energy saving potential comes with ASIC/ARM based encoding hardware, cutting the required power to 1/10 compared to CPU based encoding (Google ARGOS/NEtINT /META SVP, etc.).
Deploy Efficient Codecs: Then, be sure to use modern, efficient video codecs like H.265/HEVC or AV1 to compress video data effectively, reducing the amount of data transmitted and processed. Codecs like H.265/HEVC and AV1 are more efficient than previous ones due to advanced compression algorithms, higher compression ratios, and better motion prediction techniques. They use improved intra-frame prediction and more efficient entropy coding methods. These advancements allow them to deliver high-quality video at lower bitrates, reducing file sizes and bandwidth usage compared to older codecs like H.264/AVC.
Implement Adaptive Bitrate (ABR): Adaptive bitrate (ABR) plays a crucial role in enhancing energy efficiency for streaming services. By continuously monitoring network conditions, device type (screen resolution, processing power, display capabilities, etc.) and scene characteristics (e.g., lots of movement and detail vs. static backgrounds) it adjusts video quality in real-time, ensuring that only the necessary amount of data is transmitted. This reduces the processing power required on both the server and client sides, leading to lower energy consumption. In case of poor network performance, for example, the bitrate is lowered, conserving bandwidth and minimizing the energy used by data centers and delivery networks. This prevents wasted energy on failed buffering attempts. That efficiency extends to end-user devices, where reduced processing demands lead to lower battery consumption and extended device life. This way, adaptive bitrate not only improves the user experience by reducing buffering and interruptions but also plays a significant part in the environmental sustainability of video streaming.
Use Custom Encoding Profiles: Generate unique encoding profiles for each video title based on its specific characteristics to ensure optimal quality at the lowest possible bitrate. Speaking of macro-genres, encoding an animated movie requires managing compression artifacts and preserving vibrant colors and sharp edges. Live-action movies, on the other hand, need efficient handling of dynamic scenes, varied lighting conditions, and complex textures. Other content types like documentaries instead require balancing mixed content types, ensuring clear audio for interviews, and managing subtitles and captions. Each type necessitates tailored bitrate and codec settings to maintain quality while optimizing for streaming efficiency.
Use AI Models
AI models can significantly enhance the efficiency and effectiveness of the encoding process through intelligent analysis and automation.
Automated Scene Detection: Use AI to automatically detect and segment different types of scenes within a video, allowing for targeted encoding strategies.
Predictive Compression: Employ machine learning models to predict the optimal encoding settings based on training data from a variety of video types and encoding scenarios.
Codec Optimization: Use AI to determine the best codec and settings for each piece of content, balancing quality and compression efficiency.
Noise Reduction and Enhancement: Apply AI-driven noise reduction and enhancement techniques to improve the quality of the source video, allowing for better compression without quality loss.
Real-Time Adaptation: Use AI to analyze real-time network conditions and viewer behavior to dynamically adjust streaming quality, reducing unnecessary data transmission.
Combined Benefits
Reduced Bandwidth Usage: By optimizing encoding and packaging, less data is transmitted, leading to lower energy consumption for both data centers and end-users.
Improved Energy Efficiency: Efficient encoding reduces the processing power required, saving energy during both the encoding and streaming processes.
Enhanced Viewer Experience: Optimized data rates ensure that viewers enjoy a seamless experience without buffering (especially if in case of advertisements, these are inserted server-side), even with slower networks.
In summary, content-aware encoding and AI models make streaming more sustainable by optimizing the way video data is compressed and transmitted.
These practices reduce the amount of data that needs to be processed and sent, leading to a smooth viewing experience without interruptions and lower energy consumption with a subsequent smaller environmental footprint.
Green Video Distribution

Green streaming practices related to content distribution focus on optimizing the infrastructure and operations of delivery networks, processing, and storage to reduce environmental impact. Here is how this can be done:
Optimize Content Delivery Networks (CDNs)
Energy-Efficient CDNs: Use CDNs that operate energy-efficient data centers, better if powered by renewable energy sources like solar or wind power. Pay also attention to the hardware by deploying servers and networking equipment that are designed for low power consumption and high performance.
Geographic Distribution: Place content closer to users by using edge servers, which reduces the distance data travels and decreases latency and energy usage. Also distribute traffic evenly across servers to prevent overloading and ensure efficient use of resources.
Adaptive Delivery: Use algorithms to dynamically route content through the most efficient path, taking into account current network conditions and server loads for real-time optimization. Also implement a multi-CDN strategy by deploying different CDNs to optimize delivery routes, balance loads, and ensure redundancy, reducing the risk of outages and inefficient routing.
Improve Processing Capabilities
Efficient Processes: implement workflows that use less energy-intensive encoding methods, such as batch processing during off-peak hours when energy demand is lower. Also utilize specialized hardware, like GPUs or ARM architectures for encoding tasks, as they can perform these operations more efficiently than general-purpose CPUs. Another opportunity is represented by ASICS as they are highly optimized encoding cards and super efficient in terms of processing.
Server Utilization: Use virtual machines and containers to maximize server utilization, allowing multiple tasks to run on a single physical server and reducing idle times. Also implement serverless architectures where resources are allocated dynamically based on demand, ensuring that energy is only used when necessary.
Optimize Storage
Efficient Data Storage: Use a tiered storage approach where frequently accessed data is stored on high-speed, low-power storage devices, and less frequently accessed data is stored on energy-efficient, slower storage. Compress data and eliminate duplicates to reduce the amount of storage space required, thereby saving energy.
Eco-Friendly Cold Storage: Store infrequently accessed data using energy-efficient cold storage solutions, which use less power compared to active storage systems.
Sustainable Practices: Implement sustainable practices like data lifecycle management that ensures data is stored and deleted efficiently, reducing unnecessary storage and associated energy use. Then power storage facilities with renewable energy sources to further decrease carbon footprint.
Combined Strategies
Integrated Management: Use integrated management systems to monitor energy usage across all aspects of content distribution, processing, and storage, enabling real-time optimizations. In addition to that, implement AI-driven systems that automatically adjust resource allocation based on current demands and energy efficiency goals.
Collaborative Efforts: Adhere to industry standards and best practices for green IT and sustainable data center operations. Also collaborate with other companies and organizations to develop and share sustainable technologies and practices.
In essence, green streaming practices in content distribution, processing, and storage involve optimizing the entire infrastructure to reduce energy consumption and enhance efficiency. This includes using energy-efficient CDNs, implementing advanced processing techniques, adopting efficient storage solutions, and leveraging renewable energy sources. By focusing on these areas, streaming services can significantly lower their environmental impact while maintaining high performance and reliability.
Green Playback

Green streaming practices related to playback focus on optimizing the end-user experience to reduce energy consumption and improve efficiency. Here is how stream analytics and green streaming players contribute to these goals:
Enhance Stream Analytics
User Behavior Analysis: Analyze when and how users watch content to optimize streaming times and quality, reducing unnecessary data transmission during off-peak hours. Another recommendation would be to identify popular content and preload or cache it closer to the user to minimize repeated data transfer.
Network Optimization: Monitor network conditions in real-time to adjust streaming quality dynamically, ensuring efficient use of bandwidth and reducing buffering. Use analytics to fine-tune ABR algorithms, delivering the best possible quality at the lowest bandwidth cost based on current network conditions.
Energy Consumption Metrics: First measure energy consumption of streaming sessions to identify opportunities for optimization. Second, provide users and service providers with insights into their energy usage, encouraging more efficient streaming habits.
Deploy Green Streaming Players
Energy-Efficient Hardware: Design media players with energy-efficient components to reduce power usage during playback. Implement energy-saving features that automatically lower power consumption or put the device into sleep mode when not in use.
Optimized Software: As said, use modern, efficient video codecs like H.265/HEVC or AV1 to compress video data effectively, reducing the amount of data transmitted and processed. Integrate also adaptive streaming technologies that adjust video quality based on network conditions to avoid wasting bandwidth and energy.
Eco-Friendly Options and Energy Usage Display: Provide options for viewers to select lower resolutions or download content for offline viewing to save bandwidth and energy, at least for mobile devices. Show them real-time data on their energy consumption and offer tips for reducing it. For SmartTVs, you can encourage your audience to use solutions like FAMIUM GreenView, a green streaming software developed by Fraunhofer FOKUS that enables a more energy-efficient streaming. Their client-side solution dynamically adjusts the presentation of streaming content for energy-saving playback without modifying the original content.
Smart Content Delivery: Cache frequently accessed content locally on the device to reduce repeated data transmission and energy use. Also, allow users to schedule downloads during off-peak hours or when renewable energy sources are more available.
Software Updates: Provide regular software updates that enhance the energy efficiency and performance of the media player without requiring new hardware therefore reducing the quantity of waste.
Combined Benefits
Reduced Carbon Footprint: By optimizing both the backend (through analytics) and the frontend (through efficient players), the overall energy consumption of streaming services can be significantly reduced.
Enhanced User Experience: Efficient streaming reduces buffering and improves video quality, leading to a better viewing experience.
Cost Savings: Lower energy consumption translates to cost savings for both users and service providers.
Green streaming practices in playback involve using advanced analytics to understand and optimize user behavior and network conditions, while green streaming players are designed to be energy-efficient and user-friendly. Together, these strategies help reduce the environmental impact of streaming services, improve performance, and promote sustainable viewing habits.
These were our key recommendations for TV operators on how to reduce the emissions connected to the streaming value chain. Sustainable streaming is a hot topic for the whole industry and something Fraunhofer FOKUS institute can help your company with.
If you are in Berlin, do not miss the chance to visit their 11th Media Web Symposium, with a dedicated workshop and tutorial around green streaming! You can register for free here.
In case you want to discuss the impact of the advertising value chain, please reach out to our team as well!
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