Page 26 - Preliminary Analysis Towards a Standardized Readiness Framework - Interim Report

Preliminary Analysis Towards a Standardized Readiness Framework

Infrastructure including triggers, speed bumps, barricades, banners, advertisements, and
route planning should be considered. Additional considerations include fiber to the RSU,
computation available in the edge, wireless capabilities in the vehicle, between the vehicle
and RSU, etc.

Technologies used encompass collision avoidance, driver attention, and human detection
systems, with local innovations such as the number of patents, publications, local research,
and maturity levels manifested by validation, standards compliance, certifications, and labs
being significant.

Interoperability and human factors like awareness and training, trust, and security are vital
for successful implementation. Mapping technology use cases to regulations and policies is
essential for achieving specific safety goals, such as reducing pedestrian mortality.

4�1�16 Smart Irrigation

In modern agriculture, the integration of advanced technologies involves a diverse array of
actors and systems working together to enhance efficiency and yield optimization. Agricultural
farmers use both traditional methods and modern technology for irrigation, pesticide usage,
and farm management. Sensors are used to monitor temperature, humidity, soil moisture, fluid
levels, and mineral content in the roots, feeding data into low latency, high throughput networks
such as edge networks. AI and ML systems collect this data and infer actionable insights aligning
with policies, which are then executed by actuators such as automated irrigation systems,
tractors, and dispensers for pesticides and fertilizers. Backend cloud storage supports this
ecosystem, while dashboards provide farmers with information. Local conditions, such as water
and air quality and soil fertility, are also considered. Technologies like LoRa, LoRa-WAN, RFM69,
Bluetooth, and narrow-band IoT facilitate robust communication and low-power operations,
while AI, ML, and emerging technologies like 6G enhance data analysis and decision-making
capabilities. Ensuring interoperability between different sensors and communication systems
is crucial, as is incorporating farmers' experiences and practices to refine and adopt these
technologies effectively.

5. Future Work and Conclusion

Currently, our work captures a preliminary analysis of the Artificial Intelligence (AI) readiness
study, the goal of which is to develop a framework assessing AI readiness to indicate the ability
to reap the benefits of AI integration. By studying the different actors and characteristics in
different domains, the bottom-up approach allows us to find common patterns, metrics, and
evaluation mechanisms for the integration of AI.

The main AI readiness factors identified in this report are: Availability of open data, Access to
Research, Deployment capability along with Infrastructure, Stakeholders buy-in enabled by
Standards, Developer Ecosystem created via Opensource, Data collection and model validation
via Sandbox pilot experimental setups, Storage and computing via Core Cloud and Edge
Cloud.

In future, the number of case studies, use cases, and scenarios would be scaled to include
diverse set of domains and regions. Specifically, the following future steps are proposed:

18