The American Journal of Engineering and Technology
150
https://www.theamericanjournals.com/index.php/tajet
TYPE
Original Research
PAGE NO.
150-158
10.37547/tajet/Volume07Issue07-14
OPEN ACCESS
SUBMITED
08 June 2025
ACCEPTED
16 June 2025
PUBLISHED
29 July 2025
VOLUME
Vol.07 Issue 07 2025
CITATION
Alexander Shotov. (2025). Architectural Models for Integration of Mining
Installations into Existing IoT
‑
Controlled HVAC Systems. The American
Journal of Engineering and Technology, 7(07), 150
–
158.
https://doi.org/10.37547/tajet/Volume07Issue07-14
COPYRIGHT
© 2025 Original content from this work may be used under the terms
of the creative commons attributes 4.0 License.
Architectural Models for
Integration of Mining
Installations into Existing
IoT
‑
Controlled HVAC
Systems
Alexander Shotov
General Director of Aper.IT LLP Almaty, Kazakhstan
Abstract:
This paper examines an architectural model
for integrating mining installations into existing building
HVAC systems and urban district heating networks using
IoT control. The relevance of the study is justified by the
rapid growth in the share of low
‑
grade heat from server
farms and mining centers in the overall energy
consumption balance. The objectives are to develop a
comprehensive five
‑
level architecture for connecting
computational modules to low
‑
temperature loops; to
perform a comparative analysis of three basic schemes
(by
‑
pass, series
‑
loop, and hybrid
‑
grid) in terms of PUE
and heat utilization factor; and to formulate IoT
algorithms
for
dynamic
balancing
between
computational load and the needs of heat receivers. The
novelty of the paper lies in unifying technical, economic,
regulatory, and cybernetic aspects into a single model:
for the first time, a five
‑
layer integration structure is
proposed
—
from retrofit of heat
‑
exchange loops to an
edge
+
cloud platform and interfaces with BMS/SCADA;
the advantages of immersion cooling for direct
connection to heating systems at temperatures up to
60 °C are demonstrated; predictive algorithms based on
LightGBM for forecasting thermal load and dynamically
controlling the hash rate are described; and
recommendations are given for minimizing financial,
technological, and informational risks at all levels of the
architecture. The main findings show that, for mining
power up
to 30 % of the building’s heat demand, the
optimal scheme is the by
‑
pass with minimal intervention
in existing engineering networks; when heat power is
comparable to the object’s load, it is more advantageous
to apply the series
‑
loop with immersion cooling, yielding
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up to 98
% savings on mechanical chillers. For district
networks, the hybrid
‑
grid topology with buffer
accumulators and complex flow distribution is
preferable. OPC UA and MQTT are brought together for
assured telemetry. Digital twins and demand-response
programs bring energy efficiency and equipment
reliability. Multi-level OT security, combined with
support for financial hedging instruments, ensures
assured resilience against both cyberattacks and crypto-
market volatility. Such a paper would be of interest to
engineers designing building heating, cooling, and
ventilation systems; data center energy efficiency
specialists; as well as IoT solution developers for thermal
process management.
Keywords:
integration of mining installations; HVAC; IoT
control; immersion cooling; digital twin; thermal load
optimization; by
‑
pass; series
‑
loop; hybrid
‑
grid; OPC
UA;
MQTT; PUE; heat utilization factor; cyber
‑
physical
security
Introduction
Over the past five to seven years, server infrastructure
has transformed from an invisible electricity consumer
into a significant source of low
‑
grade heat. According to
the International Energy Agency, the total electricity
consumption of global data centers, excluding mining,
rose to 240
–
340 TWh in 2022, equivalent to
approximately 1
–
1.5% of global generation. Meanwhile,
telecommunications networks added another 260
–
360
TWh (IEA, 2023). Recognizing the resource potential of
such excess heat, regulators are shifting from voluntary
to mandatory recovery mechanisms: the new German
Energy Efficiency Act requires that all data centers
commissioned after 1 July 2026 deliver at least 10 % of
their thermal output to external heat networks, rising to
20 % from 2028 (Judge, 2023). Thus, rather than viewing
IT load solely as a cooling challenge, the industry is
increasingly treating it as a marketable thermal resource
to be integrated into existing building HVAC systems and
urban heating loops.
Practical benefits of this strategy are already
measurable. In Sweden’s capital, the
Open District
Heating scheme had connected two dozen IT sites by
2022 and annually extracts enough heat to warm around
30,000 modern apartments, reducing the network’s
specific emissions by 50 g CO₂ per kWh delivered
(European Commission, 2023). For HVAC designers, this
presents a stable source of medium-temperature heat
that can be easily incorporated via plate heat
exchangers and managed by the same IoT controllers
that govern the rest of the building’s engineering
systems.
Mining farms, in particular, offer exceptionally high
heat
‑
flux density. At the network scale, this provides a
notable contribution: Bitcoin mining consumption was
estimated by the IEA to be 110 TWh in 2022, twenty
times the 2016 level (IEA, 2023). Such concentrated
boilers are well-suited for liquid cooling: immersion
baths or coolant loops can feed radiator circuits directly,
eliminating the need for high-lift heat pumps. A pilot in
Finland
’
s Satakunta region demonstrated that even a 2
MW installation can supply heat to approximately
11,000 residents via the local district heating system
(Gooding, 2024).
Thus, excess heat from IT equipment
—
especially crypto-
mining
—
ceases to be a passive byproduct and becomes
an active element in low-carbon building architecture.
The following sections will examine how to select the
appropriate integration scheme for incorporating heat
into existing HVAC loops and which IoT algorithms to
employ to balance computational load against heat
consumer requirements.
Materials and Methodology
This section is based on an analysis of 24 sources,
including academic studies, industry reports, pilot
project case studies, and regulatory documents. Among
the works reviewed were global data
‑
center
consumption and heat
‑
recovery potential assessments
(IEA, 2023), German regulatory requirements for heat
recovery (Judge, 2023) and the EU Energy Efficiency
Directive (Uptime Intelligence, 2023), Swedish and
Finnish project experiences (European Commission,
2023; Gooding, 2024), and technical descriptions of air
and immersion cooling equipment (BitMain, 2020; Zhou
et al., 2024). Additionally, retrofit guidelines for HVAC
systems (Simmons, 2020), specifications for OPC UA and
MQTT protocols (OPC Foundation, 2024; Dave, 2024),
and research on edge+cloud platforms for predictive
control (Petri et al., 2021) were examined.
The theoretical foundation comprised assessments of
mining-module heat-flux density and their integration
into heating loops. BitMain (2020) and Zhou et al. (2024)
indicate that, in practice, immersion cooling can deliver
heat at temperatures up to 60°C. It is, therefore,
attractive for direct connections with low-temperature
systems. Alfalaval (2024) and Profile IT Solutions (2025)
provide an assessment of three topologies
—
bypass,
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series-loop, and hybrid-grid
—
regarding their capital and
operational expenditures. Meanwhile, AMR (2025) and
Uptime Intelligence (2023) assessed the scalability of
solutions at the building and district levels.
Methodologically, the work combines four approaches.
First, a comparative analysis of heat
‑
extraction
schemes: contrasting air and immersion cooling, as well
as the three architectural configurations by PUE and
heat
utilization
factor
(Alfalaval,
2024;
Profile
IT
Solutions, 2025). Second, it reviews the
regulations and industrial prescriptions in scope (Judge,
2023; Uptime Intelligence, 2023; European Commission,
2023) to synthesize criteria for ethical and safe
implementation. Third, a content analysis of pilot
cases
—
comprising the Swedish Open District Heating
scheme (European Commission, 2023) and the Finnish
Satakunta project (Gooding, 2024)
—
was conducted,
which returned heat return rates as well as impacts on
CO₂ emissions. The empirical experiment then runs
modeling using a digital twin of an HVAC system and the
LightGBM algorithm (Shi et al., 2024; Zanetti et al.,
2025), as well as thermal load forecasting models and
dynamic hash rate control strategies.
Besides the technical and regulatory reviews, the
current paper provided an economic analysis of
demand-response programs (Gracia, 2022; Riot
Platforms, 2025), a review of cyber-risk based on
incident statistics (Kaspersky, 2025), and results from a
study in chip degradation under conditions of thermal
stress (El-Sayed et al., 2012).
Results and Discussion
The integration architecture comprises five interrelated
layers, each of which must simultaneously satisfy
thermal
engineering,
electrical,
and
telemetry
constraints, ensuring that the computing node's excess
heat is converted into useful thermal power for the
building without compromising controllability. This
approach requires the coordinated selection of
equipment, protocols, and algorithms, since a change in
parameters at one layer immediately affects the
balances of the others.
At the computational
‑
source level, GPU farms and
specialized ASIC racks are distinguished. The latter
achieves a record heat-flux density: a typical Bitmain S19
Pro at a hash rate of 110 TH/s consumes approximately
3.25 kW, all of which is dissipated as heat (Bitmain,
2020). In GPU solutions, the total load is distributed
among graphics cards and fans, reducing the specific
density but providing flexibility in frequency and voltage
control. For HVAC architects, the key factor is the
method of heat extraction. With air cooling, the specific
heat flux is limited; however, immersion cooling allows
the coolant to be delivered at temperatures of up to
60 °C, which is suitable for direct connection to low
-
temperature heating circuits (Zhou et al., 2024).
The subsequent chain begins with an HVAC retrofit. In
most existing facilities, it is expedient to install plate or
rotary heat exchangers, since they do not require a
complete overhaul of shafts and can recover over 80 %
of the sensible heat from exhaust air (Simmons, 2020).
Given that the fluid temperature from immersion baths
is significantly higher than the supply temperature, a
hydraulic insert into the existing heating loop and
re
‑
tuning of VAV fans to maintain the required airflow in
the premises are sufficient.
To render the heat flux predictable, IoT infrastructure is
integrated into the loop: temperature, flow, and
vibration sensors transmit data via OPC UA or MQTT.
OPC UA defines the address space structure and mutual
device
authentication
mechanism,
ensuring
compatibility between the OT and IT layers (OPC
Foundation, 2024). In contrast, MQTT provides a
lightweight broker for event-driven messages and is
used when minimal latency or cellular-network
operation is required (Dave, 2024). A typical gateway
consolidates both protocols and translates the data into
a format understandable by the cloud or a local
processing server.
The next level hosts the management platform, where
an edge node stores second-level telemetry series,
constructs basic digital twins, and runs optimization
algorithms. Experiments on university campuses have
demonstrated that transitioning from purely cloud-
based analytics to a distributed edge and cloud
approach reduces the HVAC peak power draw through
more accurate predictive control (Petri et al., 2021). The
digital twin enables adj
ustment of the miners’ operating
point (partially disabling ASIC units or altering GPU
frequency) just enough to keep the heat
‑
receiver
demand and the PUE limit in balance.
The final layer comprises interfaces with BMS and
SCADA. Most modern building systems support
BACnet/IP; the BACnet-BMS market is projected to
reach USD 17 billion by 2025, with further annual growth
of 3
–
4%, as shown in Fig. 1 (AMR, 2025).
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Fig. 1. The BACnet Building Management System Market Size (AMR, 2025)
Modbus RTU or Modbus TCP is typically adequate for
local units. Climate equipment manufacturers currently
provide gateways that enable up to 100 Modbus devices
to be linked to a single KNX or BACnet bus without
requiring any additional programming (Trane, 2023).
Findings from an API-compatibility study revealed that
REST interfaces to BMS facilitate the integration of
external IoT platforms, thereby accelerating data
delivery to analytics by nearly a factor of two when
benchmarked
against
traditional
point-to-point
mapping (Yefi et al., 2024).
Together,
these
components
form
a
closed
technological loop in which the real
‑
time reheated
output of the miners is converted into a controllable
energy resource for the building. At the same time, open
protocols reduce integration costs and ensure solution
scalability.
At the conceptual design stage, the choice of mining-
node connection scheme to the existing HVAC system is
determined by two variables
—
the share of heat that the
building can accept without reconstructing the heat-
exchange loop, and the temperature level of that heat.
The revised EU Energy Efficiency Directive prioritizes
economic recovery by obliging all data centers to
recover heat whenever possible, or to demonstrate
technical infeasibility regarding heat extraction. If a data
center does not consume extracted heat, details must
be provided on its use in external systems (Uptime
Intelligence, 2023). An example system is illustrated in
Fig. 2. This, therefore, brings three basic topologies that
can scale the solution from one building up to a district
heating network, preserving controllability via the IoT
loop.
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Fig. 2. Data Center Waste Heat Export to District Heating Network (Uptime Intelligence, 2023)
Parallel, or by
‑
pass, configuration is intended for
buildings where mining can supply no more than
one
‑
third of the peak thermal load, thereby minimizing
intervention in the primary ventilation scheme. Hot air
or fluid from the racks is routed to a heat recovery unit
and then blended into the supply duct. When demand
drops, VAV dampers automatically open the bypass, and
the system reverts to normal operation. This approach
aligns well with regulations such as the German
Energy
Efficiency
Act, which sets a target threshold for
heat reuse of 30 % from 2024 and 40 % from 2027 for
new sites (Judge, 2023). Capital expenditures are limited
to the installation of a heat exchanger and a few sensors,
making the scheme attractive for rapidly deployable
edge nodes.
The sequential, or series
‑
loop, model is employed when
the thermal output of mining is comparable to the
facility
’
s requirements and the temperature regime
permits operation without a heat pump. The fluid, which
extracts up to 200 kW from each rack via direct crystal
cooling, returns directly to the building
’
s hydraulic
circuit after passing through a plate heat exchanger
(Alfalaval, 2024). Mechanical cooling is scarcely utilized,
and energy savings for cooling reach 98
% compared to
traditional air cooling. To maintain this regime, an IoT
platform regulates miners’ hash rate via a predictive
thermal
‑
balance model, synchronously adjusting pump
speeds and three
‑
way valve positions.
When the heat source must serve multiple buildings, a
cascade or hybrid
‑
grid scheme is preferred. In this
architecture, heat from the mining module is first stored
in a buffer accumulator, after which distribution stations
deliver it through a four
‑
pipe network to residential and
commercial buildings. A Finnish pilot provides practical
validation: a 2-MW crypto center in the Satakunta
region supplies district heating for approximately 11,000
residents by feeding thermal energy into the municipal
network (Gooding, 2024). Load distribution among
multiple consumers reduces seasonal variability but
requires additional valves, commercial metering units,
and expanded IoT-SCADA functions to balance flows in
real-time.
The final solution is selected by comparing the building’s
specific thermal load, investment constraints, and
expected equipment lifecycle. At approximately 10 MW
capacities, the shift between air and immersion cooling,
as required for a Series-Loop and a Hybrid-Grid, reduces
capital expenditure by an average of 41% with lower
annual cooling energy expenses (Profile IT Solutions,
2025). However, as the share of recovered heat
increases, the backup removal systems for thermal
network failure become more expensive. This again
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increases payback periods. Therefore, facilities with a
limited thermal share more frequently adopt the parallel
bypass, whereas new or extensively modernized
buildings with high thermal loads move to the sequential
scheme, and urban clusters with developed district
infrastructure utilize cascade networks. This matrix
approach
enables
flexible
integration
of
mining
‑
generated heat into existing HVAC landscapes
while remaining within regulatory limits for energy
efficiency and emissions.
High
‑
level algorithms link mining
‑
rack telemetry,
building heating parameters, and energy
‑
market price
signals into a unified decision
‑
making model. At its core
is a predictive thermal balance: a LightGBM
gradient
‑
boosting model trained on two seasons of
historical data achieved a mean absolute percentage
error of 6.2
% for 15
‑
minute heat
‑
load forecasts (Shi et
al., 2024), enabling the operator to reduce annual
cooling electricity consumption by 12
% without
compromising indoor climate (Zanetti et al., 2025).
When forecasts indicate a mismatch between the
potential heat output of computational modules and the
required heat supply, the system regulates the hash
rate. ERCOT practice in Texas has demonstrated the
scale of this maneuver: during extreme heat, industrial
miners synchronized shutdowns, freeing over 1,000
MW
—
i.e., more than 1 GW
—
for the grid, equivalent to
approximately 1% of the state’s peak load (Gracia,
2022).
Access to demand
‑
response programs makes such
behavior economically attractive. For example, Riot
Platforms
’
June
2025 report shows that participation in
ERCOT and MISO schemes yielded USD
1.8
million in
demand
‑
response credits and USD
3.8
million in price
credits
—
USD
5.6
million
in
total
—
reducing
the
weighted average cost of electricity to 3.4
¢
/kWh
(Riot
Platforms, 2025). These figures define the upper
bound of savings that a predictive controller can
incorporate into its objective function alongside PUE
and heat
‑
utilization metrics.
Finally,
service
‑
oriented
diagnostics
close
the
equipment sustainment loop. In a case study of a major
manufacturer implementing augmented reality for step-
by-step technician guidance, repair times decreased by
30% while error rates fell by 40%, directly improving
mining-cluster availability and reducing the risk of
unexpected thermal deficits (Fatfinger, 2024).
Together, predictive forecasting, dynamic hash-rate
adjustment,
integration
with
demand-response
programs, and service-oriented diagnostics form a self-
tuning cycle that maintains thermal and energy
efficiency at levels required by modern regulations and
business metrics.
The risk landscape of integrating mining installations
into HVAC circuits extends far beyond thermal
‑
balance
calculations:
cryptocurrency
price
fluctuations,
hardware
failures,
regulatory
constraints,
and
cyberattacks can undermine the business case even in
flawless designs. Volatility is the primary and most
obvious threat. In 2022, Bitcoin lost 65
% year
‑
on
‑
year
amid the Terra
USD collapse and FTX bankruptcy
—
the
industry
’
s worst annual performance since 2018
(McCarthy, 2022). To mitigate such downturns,
operators tie mining regimes to thermal and grid signals:
when coin prices are low and heat demand is high, the
farm continues operating for the heat
‑
network contract,
generating off
‑
exchange revenue; when excess
electricity and rising coin prices occur, a boost mode
activates, selling hash rate to the market. Cash
‑
flow gaps
are further insured by fixing part of profits in forward
electricity contracts and cryptocurrency collar options
—
a practice now employed by major public miners in
North America.
Technological risk manifests in two forms. Overheating
and thermal shock cycles accelerate chip degradation. A
server-reliability study found that for every 10°C above
21°C, the lifespan of electronic components is halved (El-
Sayed et al., 2012). Immersion cooling stabilizes crystal
temperature and acts as a humidity shield. Meanwhile,
dew-point and corrosion sensors are also integrated into
the IoT loop, along with the application of a selective
conformal lacquer to the circuit boards. At the policy
level, an N + 10% spare-rack rule allows equipment to be
worked on without removing it from the building's
thermal output.
Because mining modules generate heat continuously,
non-fulfillment of requirements is liable to be fined and
may also carry a suspension in operations. Risk can be
mitigated at the feasibility stage: a digital twin of the
HVAC scheme simulates at least three heat-demand
scenarios
—
normal, anomalously warm season, and
network-failure emergency
—
and demonstrates to
regulators the ability to dissipate power safely without
overheating. Additionally, an isolated dry
‑
cooling circuit
is reserved and automatically engaged if the fluid
temperature exceeds permissible limits.
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Cyber threats are among the critical factors. In Q4 2024
alone, Kaspersky ICS
‑
CERT recorded 107 publicly
confirmed incidents in industrial networks, 50
% of
which involved ransomware and 12
% resulting in
production
‑
line shutdowns (Kaspersky, 2025), with most
incidents occurring in the USA, as shown in Figure
3.
Fig. 3. Countries with the highest number of reported incidents (Kaspersky, 2025)
In mining
–
HVAC topologies, a breach of the OT segment
entails the simultaneous loss of hash rate and thermal
generation; therefore, segmentation according to an
east
–
west firewall principle and Zero Trust VPNs
between layers of IIoT gateways and the BMS becomes
a mandatory requirement. ASIC firmware is stored in a
repository with integrity verification, and critical PLCs
receive a unidirectional data
‑
diode channel to SCADA,
preventing any reverse writing. These measures,
together with regular red
‑
team attack simulations,
reduce intrusion detection time and limit damage to the
scope of an isolated segment.
Thus, financial, technological, regulatory, and cybernetic
risks jointly define the framework for integration
architecture. It enables a highly dispersed source to
become a vital component of low-carbon systems while
still operating, by implementing specific measures and
actions, ranging from investing in crypto to multiple
layers of OT safety.
Conclusion
This study will build a detailed model of how to fit mining
installations into existing HVAC systems with IoT control
at five related levels: starting from the computational
modules that produce heat, moving through retrofit
heat-exchange loops, including a telemetry network,
using an edge-plus-cloud management platform, and
finally ending with BMS/SCADA interfaces. The key
characteristics of various equipment types are
described
—
from high-density ASIC rigs dissipating up to
3.25 kW per device to flexible GPU farms
—
and the
benefits of immersion cooling in maintaining coolant
temperatures sufficient for direct connection to low-
temperature heating systems are demonstrated.
Meanwhile, the selection of recuperators and
adaptation of VAV fans in retrofit scenarios can achieve
up to 80 % recovery of sensible heat, minimizing capital
expenditures and the risk of interference with a
building’s primary engineering infrastructure.
Analysis of the three basic integration topologies
—
parallel (bypass), sequential (series-loop), and cascade
(hybrid-grid)
—
has shown that each is optimal under
specific conditions: the building’s recoverable thermal
-
load fraction, the coolant temperature level, and the
scale of the territorial network. The bypass
configuration is ideally suited for rapid deployment at
edge sites with moderate thermal output. The series-
loop delivers maximum energy savings on mechanical
cooling at coolant temperatures up to 60°C, and the
hybrid-grid enables solution scaling to district and
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municipal networks with buffer accumulators and
complex flow distribution. IIoT gateways supporting OPC
UA and MQTT, integration into BACnet/IP and Modbus
loops, and the implementation of digital twins and
LightGBM predictive models ensure precise balancing
between miners’ computational loads and heat
-sink
demands.
It is attentive not just technically, but also economically,
regulatorily,
and
cybersecurity-wise:
from
the
fluctuations in cryptocurrency prices and hardware
failures to requirements under the Energy Efficiency Act
and threats in the OT segment. The self-tuning cycle
proposed
—
dynamic hash-rate adjustment inclusive,
demand-response
programs,
augmented
–
reality
–
assisted service diagnostics, and multi-layered OT
protection
—
ensures minimized unplanned disruption
and financial losses. Ultimately, the integration of excess
heat from mining installations emerges not as a
byproduct of IT infrastructure but as an active resource
for low-carbon buildings and urban thermal networks,
capable of enhancing overall energy efficiency and
making a meaningful contribution to CO2 emissions
reduction.
References
1.
Alfalaval. (2024).
Innovative direct-to-chip data
center cooling system with Alfa Laval brazed heat
exchangers
.
Alfalaval.
2.
AMR.
(2025,
March
7).
BACnet
Building
Management System Strategic Insights: Analysis
2025
and
Forecasts
2033
.
AMR.
https://www.archivemarketresearch.com/reports/
bacnet-building-management-system-53302
3.
BitMain. (2020, February 27).
S19 Pro Specifications
.
BitMain.
https://support.bitmain.com/hc/en-
us/articles/900000261726-S19-Pro-Specifications
4.
Dave, D. M. (2024, May 14).
Exploring MQTT & OPC
UA: The Backbone of IoT Communication
. IoT
Business
News.
5.
El-Sayed, N., Stefanovici, I., Amvrosiadis, G., Hwang,
A. A., & Schroeder, B. (2012). Temperature
management in data centers.
Measurement and
Modeling
of
Computer
Systems
https://doi.org/10.1145/2254756.2254778
6.
European Commission. (2023, October 10).
Stockholm, Sweden: Heat recovery from data
centres
.
European
Commission.
mayors.ec.europa.eu/en/Stockholm-Heat-
recovery-from-data-centres
7.
Fatfinger. (2024, April 6).
Augmented Reality (AR) for
Real-Time Maintenance Guidance
. Fatfinger.
https://fatfinger.io/augmented-reality-ar-for-real-
time-maintenance-guidance/
8.
Gooding, M. (2024, June 20).
Marathon Digital uses
crypto mining heat to warm homes in Finland
. Data
Center
Dynamics.
9.
Gracia, M. (2022, July 12). Texas Bitcoin Miners Bail
As Record Heat Alters Economics.
Forbes
10.
IEA. (2023, July 11).
Data Centres and Data
Transmission
Networks
.
IEA.
https://www.iea.org/energy-
system/buildings/data-centres-and-data-
transmission-networks
11.
Judge, P. (2023, July 7).
Germany to Pass Energy
Efficiency Act, Demanding Heat Reuse in Data
Centers
.
Data
Center
Dynamics.
12.
Kaspersky. (2025, April 8).
A brief overview of the
main incidents in industrial cybersecurity
. Kaspersky
ICS
CERT.
13.
McCarthy, A. M. (2022, December 28).
Bitcoin
plunged 65% in 2022 as Terra and FTX went up in
flames
.
The
Block.
https://www.theblock.co/post/197109/bitcoin-
plunged-65-in-2022-as-terra-ftx-went-up-in-flames
14.
OPC Foundation. (2024).
OPC Unified Architecture
Interoperability for Industrie 4.0 and the Internet of
The American Journal of Engineering and Technology
158
https://www.theamericanjournals.com/index.php/tajet
Things
.
OPC
Foundation.
15.
Petri, I., Rana, O., Rezgui, Y., & Fadli, F. (2021). Edge
HVAC
Analytics.
Energies
,
14
(17),
5464.
https://doi.org/10.3390/en14175464
16.
Profile IT Solutions. (2025, February 27).
Understanding the Total Cost of Ownership (TCO) for
a 10 MW AI Data Center: Air Cooling vs. Immersion
Cooling
.
Profile
IT
Solutions.
17.
Riot Platforms. (2025).
Riot Announces June 2025
Production and Operations Updates
. Riot Platforms.
https://www.riotplatforms.com/riot-announces-
june-2025-production-and-operations-updates/
18.
Shi, Z., Zheng, R., Shen, R., Yang, D., Wang, G., Liu,
Y., Li, Y., & Zhao, J. (2024). Building heating load
forecasting based on the theory of transient heat
transfer and deep learning.
Energy and Buildings
,
313
,
114290.
https://doi.org/10.1016/j.enbuild.2024.114290
19.
Simmons, S. (2020).
Air-To-Air Energy Recovery
Equipment
.
ASHRAE.
https://www.ashrae.org/file%20library/technical%
20resources/covid-19/si_s20_ch26.pdf
20.
Trane. (2023).
Integration Guide on BACnet and
Modbus
Integration
.
Trane.
21.
Uptime Intelligence. (2023).
Heat reuse: a
management
primer
.
Uptime
Intelligence.
https://intelligence.uptimeinstitute.com/resource/
heat-reuse-management-primer
22.
Yefi, P., Menon, R., & Eicker, U. (2024). Evaluation of
APIs for Data Exchange with Building Management
Systems.
Proceedings of the ACM/IEEE 6th
International Workshop on Software Engineering
Research & Practices for the Internet of Things
,
6
, 1
–
https://doi.org/10.1145/3643794.3648275
23.
Zanetti, E., Blum, D., Fu, H., Weyandt, C., Pritoni, M.,
& Piette, M. A. (2025). Commercial Building HVAC
Demand Flexibility with Model Predictive Control:
Field Demonstration and Literature Insights.
Energy
and
Buildings
,
116097.
https://doi.org/10.1016/j.enbuild.2025.116097
24.
Zhou, X., Xin, Z., Tang, W., Sheng, K., & Wu, Z. (2024).
Comparative study for waste heat recovery in
immersion cooling data centers with district heating
and organic Rankine cycle (ORC).
Applied Thermal
Engineering
,
242
,
122479.
https://doi.org/10.1016/j.applthermaleng.2024.12
2479
