AI Puts the “Ability” in Sustainability

ByTodd Vierra

Sensors surround all who live in a modern city, capturing vibrations, air quality, water safety, energy usage, sights, sounds, and more. With AI, sensor-fed information is analyzed in real-time, feeding intelligent choices that enhance our quality of life.

BrainChip, an industry pioneer, enables deployment of AI “at the edge” — that is, in locations where the analysis and decisions occur at a sensor without connecting to the cloud or, in some cases, a power source. This truly unlocks the promise of portable, mobile AI. As demands for AI continue to grow, the compute and bandwidth required to support a cloud-only solution becomes economically prohibitive, making edge-based computing more critical than ever.

Neuromorphic AI is an emerging solution. that delivers extremely efficient processing by imitating the human brain. Neuromorphic solutions enable small footprint, low power, cost-effective and sustainable alternatives to traditional AI solutions.

How is neuromorphic AI critical for sustainable cities?

BrainChip has found methods to boost performance, accuracy, and efficiency by orders of magnitude, expanding AI’s edge use cases. This provides digital solutions within existing power/energy envelopes while amplifying the benefits of AI in delivering intelligent services which extend and optimize most aspects of urban life.

Auto transportation

AI can optimize traffic flow, reduce congestion, and improve transportation efficiency through real-time data analysis and predictive modeling. Sensors throughout a smart city and a V2X framework can inform smart vehicles of alternate routes. BrainChip’s recent advances in quickly identifying objects (like pedestrians) through streaming video can drastically improve safety both through intelligent vehicular control as well as traffic management.

Alternative energy

AI-driven systems can manage energy consumption in city infrastructure, optimizing lighting, heating, and cooling to reduce energy waste. Anomaly detection is used for predictive maintenance and system monitoring ensuring longer life of machinery, conserving resources, reducing downtime and reducing supply chain demands.

New agriculture

Vertical hydroponic and oceanic farms help reduce pollution and improve air quality. These cannot scale without intelligent remote sensors and automation to maintain crops of the future and urban green spaces.

Waste management

AI can optimize waste collection routes, predict when bins need emptying, and promote recycling and waste reduction initiatives. BrainChip’s collaboration with Circle8 Clean Technologies and AVID Group is entering the pilot phase in Australia to automate sorting and analyze data about consumer habits and the waste stream.

Health

Portable medical devices, EEG, EKG analyzers that quickly assess health conditions; wearable or implantable devices monitoring and analyzing vital signs that identify known predictors of health issues, not only save lives and cost for individuals by enabling preventative care, but also assists health services readiness for patient arrival, improving outcomes.

Public services

Improved Human Machine Interfaces (HMIs) with voice and vision combined with AI chatbots and virtual assistants can serve citizens to manage efficient interactions more intuitively. BrainChip's solutions have proven capability for accurate interpretation of voice commands, amongst other intelligence needed for this purpose.

Connectivity

In high density urban conditions, last mile 5G infrastructure needs energy efficient, intelligent nodes for capacity and latency through base stations and Pico cell. Connectivity through satellites is also ramping up. Edge AI is becoming a critical component in all of them.

Innovators are already applying neuromorphic AI and BrainChip is excited to partner with you to deliver on the promise and potential of this incredible technology. Share your ideas at sales@brainchip.com.

Todd Vierra is VP Customer Engagement for BrainChip, which delivers hyperefficient neuromorphic IP compute at the edge.