IEEE Consumer Electronics Magazine - March/April 2023 - 58

Special Section on Security, Trust and Services for AI-Empowered Sensing in the Next Generation IoT
algorithm to collect and deal with the ecological environment in the network environment
damage and compensation for the relevant data, and the use of the habitat equivalent
analysis method to analyze the collected experimental data, from the ecological
environment of water resources, land resources, biological resources, and damage to the
ecological environment in atmospheric resources were analyzed. Then, the legal clauses
of compensation for ecological environment damage in developed countries and China are
counted and the cases of compensation for ecological environment damage over the last
five years in China are analyzed. Most of the land resources are used for building
construction, and the proportion of land resources of houses is more than 40%, while the
proportion of land occupied by mountain forests is less than 30%. China's legal rights and
interests in compensation for ecological and environmental damage are relatively weak.
In 2016, there were only three laws in China on compensation for ecological and
environmental damage. By 2020, there were 26 laws in China, and within five years, there
were 72 laws in China on compensation for ecological and environmental damage. The
settlement rate of compensation for ecological environmental damage is 41.96%.
BACKGROUND MEANING
& IN RECENT YEARS, people's production and life
to the surrounding environment have brought
many adverse effects to the ecological environment
and are therefore subject to a lot of indelible
damage, such as the sharp decline of forest vegetation,
the extinction of many species, the shortage
of fresh water resources, the transformation of
green fields into deserts, and thedeteriorating environment.
However, in terms of China's national
conditions, the relevant legislation andlaw enforcement
of compensation for ecological environmental
damage are still relatively weak. Based on the
background of the artificial intelligence era, this
article uses neural network algorithms to collect
and process the ecological environment damage
and compensation-relateddata in the network environment,
and uses the habitat equivalent analysis
method to analyze the collected experimental
data, which can effectively understand the status
of the ecological environment. In recent years, as
the awareness of environmental protection has
increased, the recyclability of the ecosystem is
developing in a good direction step by step.
Related Work
Dong-Sheng et al.1 analyzed the damage to the
ecological environment caused by coal exploitation
in the last 10 years in Shanxi Province, and put forward
suggestions on establishing ecological compensation
mechanisms, restoring the ecological
58
environment in Shanxi. Jing et al.2 established an
indicator system for the investigation of ecological
and environmental damage caused by oil spill and
water pollution events in the sea area near the
Changjiang estuary in Chongqing by taking oil spill
and water pollution events as an example. Zhixiang
et al.3 defined the legal liability for compensation
for ecological environmental damage, and discussed
the principle of attribution of legal liability
for ecological environmental damage, constitutive
elements, and exemption grounds. Qiulian et al.4
found that the water environment in some river
basins in China is severely damaged. Qiulian briefly
analyzed the ecological compensation strategies
for severely damaging the water environment in
the river basin; the aim was to make relevant compensation
strategies play their due roles; measure
the carrying capacity of the environmental system
fromtheperspectiveofproduction; and study complex
ecosystems and economic systems, thereby
improving the economic benefits of the entire ecosystem
environment.5
RELEVANT METHODS AND
TECHNOLOGIES FOR ECOLOGICAL
ENVIRONMENT DAMAGE
COMPENSATION MANAGEMENT
Artificial Intelligence
Artificial intelligence is a science and technology
that extends and expands the simulation
of human intelligence behavior based on the
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