import streamlit as st
def app():
with open('style.css') as f:
st.markdown(f"", unsafe_allow_html=True)
st.markdown("
Litter Monitoring Cockpit
",
unsafe_allow_html=True)
st.markdown("The Litter Monitoring Cockpit is an open-source\
digital tool which aims to assist urban waste management planners and \
other users in identifying and tracking relevant \
litter hotspots from various non-traditional data sources.
",
unsafe_allow_html=True)
footer = """
"""
st.markdown(footer, unsafe_allow_html=True)
c1, c2, c3 = st.columns([8,1,12])
with c1:
st.image("docStore/img/vision.png")
with c3:
st.markdown('Todays litter monitoring systems often forego \
the vast potential of data transparency. Here, we present a new approach to data-driven litter \
monitoring.
',
unsafe_allow_html=True)
intro = """
For this purpose, the PREVENT Waste Alliance formed a project team \
to develop this AI-powered open-source web application that helps identify and monitor \
litter hotspots in various regions faster to facilitate \
evidence-based decision-making processes in sustainable development and beyond.
This tool allows urban waste management planners and other users the possibility to rapidly \
identify litter hotspots in their regions, monitor their evolution, and inform holistic \
mitigation strategies for waste leakage. To understand the application's functionalities \
and learn more about the project, see the attached concept note.
"""
st.markdown(intro, unsafe_allow_html=True)