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eaglelandsonce
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24a1d58
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Parent(s):
1040745
Update app.py
Browse files
app.py
CHANGED
@@ -180,6 +180,25 @@ I use it all the time Mohammad says, I even bought my breakfast this morning fro
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"""
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# Function to draw the grid with optional highlighting
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def draw_grid(data, highlight_coords=None):
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with col2:
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st.
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if sensors: # Check if there are sensors to display
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graph_store = TripleStore()
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image = Image.open('./data/incentive_image.jpg')
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st.image(image, caption='Sensor Insentive Program')
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@@ -665,6 +684,14 @@ with tab3:
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with tab4:
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st.header("Agent")
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with tab5:
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st.header("Control Room")
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"""
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query4 = """ ***Using Agents***
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Mohammad and Elian make their way to the Green Space, a serene area equipped with soil moisture sensors, smart irrigation systems,
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and comprehensive environmental monitoring sensors. Over a light lunch amidst the verdant surroundings, their conversation delves
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deeper into the innovative incentive program. Mohammad, with his vast knowledge, shares insights while Elian absorbs every detail,
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eager to learn more about the cutting-edge initiatives.
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Mohammad reveals an intriguing aspect of their data analysis and optimization process, introducing the support of Antropic and
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Gemini agents provided by the Aya data system. These agents are designed to assist in optimizing what is referred to as a HIN
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number—a metric that encapsulates the balance between real-life observations and their digital simulations. The HIN number is
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calculated as groundedness times hallucination, where groundedness measures the comprehensiveness of sensor data in depicting
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reality, and hallucination assesses the accuracy of AI predictions based on that data. A low HIN number could result from insufficient
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sensor coverage (reducing groundedness) or inadequately calibrated sensors or AI (increasing hallucination). Mohammad suggests
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leveraging the Antropic and Gemini agents to not only optimize the lighting within the Green Space but also to evaluate the need for
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additional sensors, aiming for an optimal HIN number that ensures both high groundedness and minimal hallucination, thereby
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enhancing the accuracy and reliability of their environmental monitoring and resource management efforts.
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"""
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# Function to draw the grid with optional highlighting
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def draw_grid(data, highlight_coords=None):
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with col2:
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st.title("Sensor Nodes")
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if sensors: # Check if there are sensors to display
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graph_store = TripleStore()
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image = Image.open('./data/incentive_image.jpg')
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st.image(image, caption='Sensor Insentive Program')
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with tab4:
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st.header("Agent")
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with tab5:
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st.header("Control Room")
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